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Lu Y, Cao Y, Tang X, Hu N, Wang Z, Xu P, Hua Z, Wang Y, Su Y, Guo Y. Deep learning-assisted mass spectrometry imaging for preliminary screening and pre-classification of psychoactive substances. Talanta 2024; 272:125757. [PMID: 38368831 DOI: 10.1016/j.talanta.2024.125757] [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: 09/25/2023] [Revised: 01/28/2024] [Accepted: 02/05/2024] [Indexed: 02/20/2024]
Abstract
Currently, it is of great urgency to develop a rapid pre-classification and screening method for suspected drugs as the constantly springing up of new psychoactive substances. In most researches, psychoactive substances classification approaches depended on the similar chemical structures and pharmacological action with known drugs. Such approaches could not face the complicated circumstance of emerging new psychoactive substances. Herein, mass spectrometry imaging and convolutional neural networks (CNN) were used for preliminary screening and pre-classification of suspected psychoactive substances. Mass spectrometry imaging was performed simultaneously on two brain slices as one was from blank group and another one was from psychoactive substance-induced group. Then, fused neurotransmitter variation mass spectrometry images (Nv-MSIs) reflecting the difference of neurotransmitters between two slices were achieved through two homemade programs. A CNN model was developed to classify the Nv-MSIs. Compared with traditional classification methods, CNN achieved better estimation accuracy and required minimal data preprocessing. Also, the specific region on Nv-MSIs and weight of each neurotransmitter that affected the classification most could be unraveled by CNN. Finally, the method was successfully applied to assist the identification of a new psychoactive substance seized recently. This sample was identified as cannabinoids, which greatly promoted the screening process.
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Affiliation(s)
- Yingjie Lu
- Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Shanghai, 201203, China; Department of Pharmacognosy, School of Pharmacy, Naval Medical University, Shanghai, 200433, China
| | - Yuqi Cao
- Technical Centre, Shanghai Tobacco (Group) Corp., Shanghai, 200082, China
| | - Xiaohang Tang
- Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Shanghai, 201203, China
| | - Na Hu
- Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Shanghai, 201203, China
| | - Zhengyong Wang
- Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Shanghai, 201203, China
| | - Peng Xu
- Key Laboratory of Drug Monitoring and Control, Drug Intelligence and Forensic Center, Ministry of Public Security, Beijing, 100193, China
| | - Zhendong Hua
- Key Laboratory of Drug Monitoring and Control, Drug Intelligence and Forensic Center, Ministry of Public Security, Beijing, 100193, China
| | - Youmei Wang
- Key Laboratory of Drug Monitoring and Control, Drug Intelligence and Forensic Center, Ministry of Public Security, Beijing, 100193, China.
| | - Yue Su
- Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Shanghai, 201203, China.
| | - Yinlong Guo
- State Key Laboratory of Organometallic Chemistry and National Center for Organic Mass Spectrometry in Shanghai, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, 200032, China.
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Xu G, Gan S, Guo B, Yang L. Application of clustering strategy for automatic segmentation of tissue regions in mass spectrometry imaging. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2024; 38:e9717. [PMID: 38389435 DOI: 10.1002/rcm.9717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 01/19/2024] [Accepted: 01/21/2024] [Indexed: 02/24/2024]
Abstract
RATIONALE Mass spectrometry imaging (MSI) has been widely used in biomedical research fields. Each pixel in MSI consists of a mass spectrum that reflects the molecule feature of the tissue spot. Because MSI contains high-dimensional datasets, it is highly desired to develop computational methods for data mining and constructing tissue segmentation maps. METHODS To visualize different tissue regions based on mass spectrum features and improve the efficiency in processing enormous data, we proposed a computational strategy that consists of four procedures including preprocessing, data reduction, clustering, and quantitative validation. RESULTS In this study, we examined the combination of t-distributed stochastic neighbor embedding (t-SNE) and hierarchical clustering (HC) for MSI data analysis. Using publicly available MSI datasets, one dataset of mouse urinary bladder, and one dataset of human colorectal cancer, we demonstrated that the generated tissue segmentation maps from this combination were superior to other data reduction and clustering algorithms. Using the staining image as a reference, we assessed the performance of clustering algorithms with external and internal clustering validation measures, including purity, adjusted Rand index (ARI), Davies-Bouldin index (DBI), and spatial aggregation index (SAI). The result indicated that SAI delivered excellent performance for automatic segmentation of tissue regions in MSI. CONCLUSIONS We used a clustering algorithm to construct tissue automatic segmentation in MSI datasets. The performance was evaluated by comparing it with the stained image and calculating clustering validation indexes. The results indicated that SAI is important for automatic tissue segmentation in MSI, different from traditional clustering validation measures. Compared to the reports that used internal clustering validation measures such as DBI, our method offers more effective evaluation of clustering results for MSI segmentation. We envision that the proposed automatic image segmentation strategy can facilitate deep learning in molecular feature extraction and biomarker discovery for the biomedical applications of MSI.
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Affiliation(s)
- Guang Xu
- College of Computer, Hubei University of Education, Wuhan, China
| | - Shengfeng Gan
- College of Computer, Hubei University of Education, Wuhan, China
| | - Bo Guo
- College of Computer, Hubei University of Education, Wuhan, China
| | - Li Yang
- College of Computer, Hubei University of Education, Wuhan, China
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Bi S, Wang M, Pu Q, Yang J, Jiang N, Zhao X, Qiu S, Liu R, Xu R, Li X, Hu C, Yang L, Gu J, Du D. Multi-MSIProcessor: Data Visualizing and Analysis Software for Spatial Metabolomics Research. Anal Chem 2024; 96:339-346. [PMID: 38102989 DOI: 10.1021/acs.analchem.3c04192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2023]
Abstract
Mass spectrometry imaging (MSI) has emerged as a revolutionary analytical strategy in biomedical research for molecular visualization. By linking the characterization of functional metabolites with tissue architecture, it is now possible to reveal unknown biological functions of tissues. However, due to the complexity and high dimensionality of MSI data, mining bioinformatics-related peaks from batch MSI data sets and achieving complete spatially resolved metabolomics analysis remain a great challenge. Here, we propose novel MSI data processing software, Multi-MSIProcessor (MMP), which integrates the data read-in, MSI visualization, processed data preservation, and biomarker discovery functions. The MMP focuses on the AFADESI-MSI data platform but also supports mzXML and imzmL data input formats for compatibility with data generated by other MSI platforms such as MALDI/SIMS-MSI. MMP enables deep mining of batch MSI data and has flexible adaptability with the source code opened that welcomes new functions and personalized analysis strategies. Using multiple clinical biosamples with complex heterogeneity, we demonstrated that MMP can rapidly establish complete MSI analysis workflows, assess batch sample data quality, screen and annotate differential MS peaks, and obtain abnormal metabolic pathways. MMP provides a novel platform for spatial metabolomics analysis of multiple samples that could meet the diverse analysis requirements of scholars.
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Affiliation(s)
- Siwei Bi
- Department of Plastic and Burn Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Manjiangcuo Wang
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
| | - Qianlun Pu
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
| | - Jinxi Yang
- West China Centre of Excellence for Pancreatitis, Institute of Integrated Traditional Chinese and Western Medicine, West China Hospital/West China Medical School, Sichuan University, Chengdu 610041, China
| | - Na Jiang
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
| | - Xueshan Zhao
- Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Siyuan Qiu
- Division of Gastrointestinal Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu,Sichuan 610041, China
| | - Ruiqi Liu
- Department of Plastic and Burn Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Renjie Xu
- Department of Respiratory Health West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xia Li
- West China School of Nursing, Sichuan University, Chengdu, Sichuan 610041, China
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Chenggong Hu
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Lie Yang
- Division of Gastrointestinal Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu,Sichuan 610041, China
| | - Jun Gu
- Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Dan Du
- Advanced Mass Spectrometry Center, Research Core Facility, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610213, China
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Li X, Zang Q, Zhu Y, Tu X, Liu J, Li T, Zhu S, Wang L, Abliz Z, Zhang R. Database-Driven Spatially Resolved Lipidomics Highlights Heterogeneous Metabolic Alterations in Type 2 Diabetic Mice. Anal Chem 2023; 95:18691-18696. [PMID: 38088904 DOI: 10.1021/acs.analchem.3c03765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Spatially resolved lipidomics is pivotal for detecting and interpreting lipidomes within spatial contexts using the mass spectrometry imaging (MSI) technique. However, comprehensive and efficient lipid identification in MSI remains challenging. Herein, we introduce a high-coverage, database-driven approach combined with air-flow-assisted desorption electrospray ionization (AFADESI)-MSI to generate spatial lipid profiles across whole-body mice. Using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), we identified 2868 unique lipids in the serum and various organs of mice. Subsequently, we systematically evaluated the distinct ionization properties of the lipids between LC-MS and MSI and created a detailed MSI database containing 14 123 ions. This method enabled the visualization of aberrant fatty acid and phospholipid metabolism across organs in a diabetic mouse model. As a powerful extension incorporated into the MSIannotator tool, our strategy facilitates the rapid and accurate annotation of lipids, providing new research avenues for probing spatially resolved heterogeneous metabolic changes in response to diseases.
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Affiliation(s)
- Xinzhu Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Qingce Zang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Ying Zhu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Xinyi Tu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jialin Liu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Ting Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Shiyu Zhu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Lingzhi Wang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), National Ethnic Affairs Commission, Beijing 100081, China
- Center for Imaging and Systems Biology, College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
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Chen Y, Liu Y, Li X, He Y, Li W, Peng Y, Zheng J. Recent Advances in Mass Spectrometry-Based Spatially Resolved Molecular Imaging of Drug Disposition and Metabolomics. Drug Metab Dispos 2023; 51:1273-1283. [PMID: 37295949 DOI: 10.1124/dmd.122.001069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 05/04/2023] [Accepted: 05/17/2023] [Indexed: 06/12/2023] Open
Abstract
Mass spectrometric imaging is a nontargeted, tag-free, high-throughput, and highly responsive analytical approach. The highly accurate molecular visualization detection technology enables qualitative and quantitative analyses of biologic tissues or cells scanned by mass spectrometry in situ, extracting known and unknown multiple compounds, and simultaneously assessing relative contents of targeting molecules by monitoring their molecular ions and pinpointing the spatial locations of those molecules distributed. Five mass spectrometric imaging techniques and their characteristics are introduced in the review, including matrix-assisted laser desorption ionization mass spectrometry, secondary ion mass spectrometry, desorption electrospray ionization mass spectrometry, laser ablation electrospray ionization mass spectrometry, and laser ablation inductively coupled plasma mass spectrometry. The mass spectrometry-based techniques provide the possibility for spatial metabolomics with the capability of high throughput and precision detection. The approaches have been widely employed to spatially image not only metabolome of endogenous amino acids, peptides, proteins, neurotransmitters, and lipids but also the disposition of exogenous chemicals, such as pharmaceutical agents, environmental pollutants, toxicants, natural products, and heavy metals. The techniques also provide us with spatial distribution imaging of analytes in single cells, tissue microregions, organs, and whole animals. SIGNIFICANCE STATEMENT: The review article includes an overview of five commonly used mass spectrometers for spatial imaging and describes the advantages and disadvantages of each. Examples of the technology applications cover drug disposition, diseases, and omics. Technical aspects of relative and absolute quantification by mass spectrometric imaging and challenges for future new applications are discussed as well. The reviewed knowledge may benefit the development of new drugs and provide a better understanding of biochemical processes related to physiology and diseases.
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Affiliation(s)
- Yu Chen
- State Key Laboratory of Functions and Applications of Medicinal Plants, Key Laboratory of Pharmaceutics of Guizhou Province, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); School of Basic Medicine, School of Pharmacy, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); Division of Pain Management, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C.); and Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, Liaoning, P.R. China (Y.P., J.Z.)
| | - Ying Liu
- State Key Laboratory of Functions and Applications of Medicinal Plants, Key Laboratory of Pharmaceutics of Guizhou Province, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); School of Basic Medicine, School of Pharmacy, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); Division of Pain Management, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C.); and Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, Liaoning, P.R. China (Y.P., J.Z.)
| | - Ximei Li
- State Key Laboratory of Functions and Applications of Medicinal Plants, Key Laboratory of Pharmaceutics of Guizhou Province, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); School of Basic Medicine, School of Pharmacy, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); Division of Pain Management, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C.); and Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, Liaoning, P.R. China (Y.P., J.Z.)
| | - Yan He
- State Key Laboratory of Functions and Applications of Medicinal Plants, Key Laboratory of Pharmaceutics of Guizhou Province, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); School of Basic Medicine, School of Pharmacy, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); Division of Pain Management, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C.); and Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, Liaoning, P.R. China (Y.P., J.Z.)
| | - Weiwei Li
- State Key Laboratory of Functions and Applications of Medicinal Plants, Key Laboratory of Pharmaceutics of Guizhou Province, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); School of Basic Medicine, School of Pharmacy, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); Division of Pain Management, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C.); and Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, Liaoning, P.R. China (Y.P., J.Z.)
| | - Ying Peng
- State Key Laboratory of Functions and Applications of Medicinal Plants, Key Laboratory of Pharmaceutics of Guizhou Province, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); School of Basic Medicine, School of Pharmacy, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); Division of Pain Management, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C.); and Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, Liaoning, P.R. China (Y.P., J.Z.)
| | - Jiang Zheng
- State Key Laboratory of Functions and Applications of Medicinal Plants, Key Laboratory of Pharmaceutics of Guizhou Province, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); School of Basic Medicine, School of Pharmacy, Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C., Y.L., X.L., Y.H., W.L.); Division of Pain Management, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, P.R. China (Y.C.); and Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, Liaoning, P.R. China (Y.P., J.Z.)
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Pu W, Wang X, Zhong X, Zhao D, Zeng Z, Cai W, Zhong Y, Huang J, Tang D, Dai Y. Dysregulation of lipid metabolism in the pseudolobule promotes region-specific autophagy in hepatitis B liver cirrhosis. Hepatol Commun 2023; 7:e0187. [PMID: 37486962 PMCID: PMC10368385 DOI: 10.1097/hc9.0000000000000187] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 03/21/2023] [Indexed: 07/26/2023] Open
Abstract
BACKGROUND Chronic hepatitis B (CHB) infection leads to liver cirrhosis (LC), the end stage of liver fibrosis. The precise diagnosis and effective therapy for hepatitis B cirrhosis are still lacking. It is highly necessary to elucidate the metabolic alteration, especially the spatial distribution of metabolites, in LC progression. METHODS In this study, LC-MS/MS together with an airflow-assisted ionization mass spectrometry imaging system was applied to analyze and compare the metabolites' spatial distribution in healthy control (HC) and hepatitis B LC tissue samples. The liver samples were further divided into several subregions in HC and LC groups based on the anatomical characteristics and clinical features. RESULTS Both the LC-MS/MS and mass spectrometry imaging results indicated separated metabolite clusters between the HC and LC groups. The differential metabolites were mainly concentrated in lipid-like molecules and amino acids. The phosphatidylcholines (PCs), lysoPCs, several fatty acids, and amino acids reduced expression in the LC group with region specific. Acyl-CoA thioesterase 2 and choline/ethanolamine phosphotransferase 1, which regulate PC and fatty acid metabolism, were significantly decreased in the pseudolobule. Meanwhile, the increased expression of LC3B and p62 in the pseudolobule indicated the upregulation of autophagy. CONCLUSIONS Hepatitis B LC induced region-specific autophagy by increasing the expression of LC3B and p62 in the pseudolobule and by dysregulation of unsaturated fatty acids, amino acids, and PC metabolism. The mass spectrometry imaging system provided additional metabolites' spatial information, which can promote biomarker screening technology and support the exploration of novel mechanisms in LC.
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Affiliation(s)
- Wenjun Pu
- Clinical Medical Research Center, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
- The First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Xi Wang
- The First Affiliated Hospital (Shenzhen People's Hospital), Southern University of Science and Technology, Shenzhen, China
| | - Xiaoni Zhong
- Clinical Medical Research Center, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
| | - Dong Zhao
- Department of Nephrology Center, Department of Liver Transplant Center, The Third People's Hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Zhipeng Zeng
- Clinical Medical Research Center, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
| | - Wanxia Cai
- Clinical Medical Research Center, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
| | - Yafang Zhong
- Clinical Medical Research Center, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
| | - Jianrong Huang
- Department of Nephrology Center, Department of Liver Transplant Center, The Third People's Hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Donge Tang
- Clinical Medical Research Center, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
| | - Yong Dai
- Clinical Medical Research Center, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
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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: 1] [Impact Index Per Article: 1.0] [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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Sun C, Wang A, Zhou Y, Chen P, Wang X, Huang J, Gao J, Wang X, Shu L, Lu J, Dai W, Bu Z, Ji J, He J. Spatially resolved multi-omics highlights cell-specific metabolic remodeling and interactions in gastric cancer. Nat Commun 2023; 14:2692. [PMID: 37164975 PMCID: PMC10172194 DOI: 10.1038/s41467-023-38360-5] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 04/27/2023] [Indexed: 05/12/2023] Open
Abstract
Mapping tumor metabolic remodeling and their spatial crosstalk with surrounding non-tumor cells can fundamentally improve our understanding of tumor biology, facilitates the designing of advanced therapeutic strategies. Here, we present an integration of mass spectrometry imaging-based spatial metabolomics and lipidomics with microarray-based spatial transcriptomics to hierarchically visualize the intratumor metabolic heterogeneity and cell metabolic interactions in same gastric cancer sample. Tumor-associated metabolic reprogramming is imaged at metabolic-transcriptional levels, and maker metabolites, lipids, genes are connected in metabolic pathways and colocalized in the heterogeneous cancer tissues. Integrated data from spatial multi-omics approaches coherently identify cell types and distributions within the complex tumor microenvironment, and an immune cell-dominated "tumor-normal interface" region where tumor cells contact adjacent tissues are characterized with distinct transcriptional signatures and significant immunometabolic alterations. Our approach for mapping tissue molecular architecture provides highly integrated picture of intratumor heterogeneity, and transform the understanding of cancer metabolism at systemic level.
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Affiliation(s)
- Chenglong Sun
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
- Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China
- Key Laboratory for Natural Active Pharmaceutical Constituents Research in Universities of Shandong Province, School of Pharmaceutical Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China
| | - Anqiang Wang
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, 100142, China
| | - Yanhe Zhou
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Panpan Chen
- Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China
- Key Laboratory for Natural Active Pharmaceutical Constituents Research in Universities of Shandong Province, School of Pharmaceutical Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China
| | - Xiangyi Wang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Jianpeng Huang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Jiamin Gao
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Xiao Wang
- Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China
- Key Laboratory for Natural Active Pharmaceutical Constituents Research in Universities of Shandong Province, School of Pharmaceutical Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China
| | - Liebo Shu
- Shanghai Luming Biological Technology co.Ltd, Shanghai, 201102, China
| | - Jiawei Lu
- Shanghai Luming Biological Technology co.Ltd, Shanghai, 201102, China
| | - Wentao Dai
- NHC Key Lab of Reproduction Regulation (Shanghai Institute for Biomedical and Pharmaceutical Technologies) & Shanghai Engineering Research Center of Pharmaceutical Translation, Fudan University, Shanghai, 200080, China.
- Shanghai Key Laboratory of Gastric Neoplasms, Department of General Surgery, Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Zhaode Bu
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, 100142, China.
| | - Jiafu Ji
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, 100142, China.
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
- NMPA Key Laboratory of safety research and evaluation of Innovative Drug, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China.
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9
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Embracing lipidomics at single-cell resolution: Promises and pitfalls. Trends Analyt Chem 2023. [DOI: 10.1016/j.trac.2023.116973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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10
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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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11
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Harvey DJ. Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018. MASS SPECTROMETRY REVIEWS 2023; 42:227-431. [PMID: 34719822 DOI: 10.1002/mas.21721] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 07/26/2021] [Accepted: 07/26/2021] [Indexed: 06/13/2023]
Abstract
This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.
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Affiliation(s)
- David J Harvey
- Nuffield Department of Medicine, Target Discovery Institute, University of Oxford, Oxford, UK
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12
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Hu H, Laskin J. Emerging Computational Methods in Mass Spectrometry Imaging. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2203339. [PMID: 36253139 PMCID: PMC9731724 DOI: 10.1002/advs.202203339] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/17/2022] [Indexed: 05/10/2023]
Abstract
Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.
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Affiliation(s)
- Hang Hu
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN47907USA
| | - Julia Laskin
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN47907USA
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13
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Ma S, Leng Y, Li X, Meng Y, Yin Z, Hang W. High spatial resolution mass spectrometry imaging for spatial metabolomics: Advances, challenges, and future perspectives. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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14
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Jin B, Pang X, Zang Q, Ga M, Xu J, Luo Z, Zhang R, Shi J, He J, Abliz Z. Spatiotemporally resolved metabolomics and isotope tracing reveal CNS drug targets. Acta Pharm Sin B 2022; 13:1699-1710. [PMID: 37139420 PMCID: PMC10149982 DOI: 10.1016/j.apsb.2022.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/05/2022] [Accepted: 10/26/2022] [Indexed: 11/11/2022] Open
Abstract
Deconvolution of potential drug targets of the central nervous system (CNS) is particularly challenging because of the complicated structure and function of the brain. Here, a spatiotemporally resolved metabolomics and isotope tracing strategy was proposed and demonstrated to be powerful for deconvoluting and localizing potential targets of CNS drugs by using ambient mass spectrometry imaging. This strategy can map various substances including exogenous drugs, isotopically labeled metabolites, and various types of endogenous metabolites in the brain tissue sections to illustrate their microregional distribution pattern in the brain and locate drug action-related metabolic nodes and pathways. The strategy revealed that the sedative-hypnotic drug candidate YZG-331 was prominently distributed in the pineal gland and entered the thalamus and hypothalamus in relatively small amounts, and can increase glutamate decarboxylase activity to elevate γ-aminobutyric acid (GABA) levels in the hypothalamus, agonize organic cation transporter 3 to release extracellular histamine into peripheral circulation. These findings emphasize the promising capability of spatiotemporally resolved metabolomics and isotope tracing to help elucidate the multiple targets and the mechanisms of action of CNS drugs.
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Affiliation(s)
- Bo Jin
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Xuechao Pang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Qingce Zang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Man Ga
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jing Xu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Zhigang Luo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jiangong Shi
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- NMPA Key Laboratory for Safety Research and Evaluation of Innovative Drug, Beijing 100050, China
- Corresponding authors.
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), National Ethnic Affairs Commission, Beijing 100081, China
- Key Laboratory of Ethnomedicine of Ministry of Education, School of Pharmacy, Minzu University of China, Beijing 100081, China
- Corresponding authors.
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15
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Huang J, Gao S, Wang K, Zhang J, Pang X, Shi J, He J. Design and characterizing of robust probes for enhanced mass spectrometry imaging and spatially resolved metabolomics. CHINESE CHEM LETT 2022. [DOI: 10.1016/j.cclet.2022.107865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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16
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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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17
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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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18
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Ablat N, Ablimit M, Sun Y, Zhao X, Pu X. Application of new imaging methods in the development of Chinese medicine. Biomed Pharmacother 2022; 153:113470. [DOI: 10.1016/j.biopha.2022.113470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 07/21/2022] [Accepted: 07/23/2022] [Indexed: 11/27/2022] Open
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19
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Zhu Y, Zang Q, Luo Z, He J, Zhang R, Abliz Z. An Organ-Specific Metabolite Annotation Approach for Ambient Mass Spectrometry Imaging Reveals Spatial Metabolic Alterations of a Whole Mouse Body. Anal Chem 2022; 94:7286-7294. [PMID: 35548855 DOI: 10.1021/acs.analchem.2c00557] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Rapid and accurate metabolite annotation in mass spectrometry imaging (MSI) can improve the efficiency of spatially resolved metabolomics studies and accelerate the discovery of reliable in situ disease biomarkers. To date, metabolite annotation tools in MSI generally utilize isotopic patterns, but high-throughput fragmentation-based identification and biological and technical factors that influence structure elucidation are active challenges. Here, we proposed an organ-specific, metabolite-database-driven approach to facilitate efficient and accurate MSI metabolite annotation. Using data-dependent acquisition (DDA) in liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) to generate high-coverage product ions, we identified 1620 unique metabolites from eight mouse organs (brain, liver, kidney, heart, spleen, lung, muscle, and pancreas) and serum. Following the evaluation of the adduct form difference of metabolite ions between LC-MS and airflow-assisted desorption electrospray ionization (AFADESI)-MSI and deciphering organ-specific metabolites, we constructed a metabolite database for MSI consisting of 27,407 adduct ions. An automated annotation tool, MSIannotator, was then created to conduct metabolite annotation in the MSI dataset with high efficiency and confidence. We applied this approach to profile the spatially resolved landscape of the whole mouse body and discovered that metabolites were distributed across the body in an organ-specific manner, which even spanned different mouse strains. Furthermore, the spatial metabolic alteration in diabetic mice was delineated across different organs, exhibiting that differentially expressed metabolites were mainly located in the liver, brain, and kidney, and the alanine, aspartate, and glutamate metabolism pathway was simultaneously altered in these three organs. This approach not only enables robust metabolite annotation and visualization on a body-wide level but also provides a valuable database resource for underlying organ-specific metabolic mechanisms.
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Affiliation(s)
- Ying Zhu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Qingce Zang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Zhigang Luo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.,Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), National Ethnic Affairs Commission, Beijing 100081, China.,Center for Imaging and Systems Biology, College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
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20
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Huang L, Nie L, Dai Z, Dong J, Jia X, Yang X, Yao L, Ma SC. The application of mass spectrometry imaging in traditional Chinese medicine: a review. Chin Med 2022; 17:35. [PMID: 35248086 PMCID: PMC8898510 DOI: 10.1186/s13020-022-00586-8] [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] [Received: 12/16/2021] [Accepted: 02/22/2022] [Indexed: 08/26/2023] Open
Abstract
AbstractMass spectrometry imaging is a frontier technique which connects classical mass spectrometry with ion imaging. Various types of chemicals could be visualized in their native tissues using mass spectrometry imaging. Up to now, the most commonly applied mass spectrometry imaging techniques are matrix assisted laser desorption ionization mass spectrometry imaging, desorption electrospray ionization mass spectrometry imaging and secondary ion mass spectrometry imaging. This review gives an introduction to the principles, development and applications of commonly applied mass spectrometry imaging techniques, and then illustrates the application of mass spectrometry imaging in the investigation of traditional Chinese medicine. Recently, mass spectrometry imaging has been adopted to explore the spatial distribution of endogenous metabolites in traditional Chinese medicine. Data collected from mass spectrometry imaging can be further utilized to search for marker components of traditional Chinese medicine, discover new compounds from traditional herbs, and differentiate between medicinal plants that are similar in botanical features. Moreover, mass spectrometry imaging also plays a role in revealing the pharmacological and toxicological mechanisms of traditional Chinese medicine.
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21
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Liu D, Huang J, Gao S, Jin H, He J. A temporo-spatial pharmacometabolomics method to characterize pharmacokinetics and pharmacodynamics in the brain microregions by using ambient mass spectrometry imaging. Acta Pharm Sin B 2022; 12:3341-3353. [PMID: 35967273 PMCID: PMC9366215 DOI: 10.1016/j.apsb.2022.03.018] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 03/10/2022] [Accepted: 03/20/2022] [Indexed: 11/01/2022] Open
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22
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Huang L, Mao X, Sun C, Li T, Song X, Li J, Gao S, Zhang R, Chen J, He J, Abliz Z. Molecular Pathological Diagnosis of Thyroid Tumors Using Spatially Resolved Metabolomics. Molecules 2022; 27:molecules27041390. [PMID: 35209182 PMCID: PMC8876246 DOI: 10.3390/molecules27041390] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 02/11/2022] [Accepted: 02/11/2022] [Indexed: 02/04/2023] Open
Abstract
The pathological diagnosis of benign and malignant follicular thyroid tumors remains a major challenge using the current histopathological technique. To improve diagnosis accuracy, spatially resolved metabolomics analysis based on air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) technique was used to establish a molecular diagnostic strategy for discriminating four pathological types of thyroid tumor. Without any specific labels, numerous metabolite features with their spatial distribution information can be acquired by AFADESI-MSI. The underlying metabolic heterogeneity can be visualized in line with the cellular heterogeneity in native tumor tissue. Through micro-regional feature extraction and in situ metabolomics analysis, three sets of metabolic biomarkers for the visual discrimination of benign follicular adenoma and differentiated thyroid carcinomas were discovered. Additionally, the automated prediction of tumor foci was supported by a diagnostic model based on the metabolic profile of 65 thyroid nodules. The model prediction accuracy was 83.3% when a test set of 12 independent samples was used. This diagnostic strategy presents a new way of performing in situ pathological examinations using small molecular biomarkers and provides a model diagnosis for clinically indeterminate thyroid tumor cases.
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Affiliation(s)
- Luojiao Huang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Xinxin Mao
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China;
| | - Chenglong Sun
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Tiegang Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Xiaowei Song
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Jiangshuo Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Shanshan Gao
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
- NMPA Key Laboratory for Safety Research and Evaluation of Innovative Drug, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jie Chen
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China;
- Correspondence: (J.C.); (J.H.)
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
- NMPA Key Laboratory for Safety Research and Evaluation of Innovative Drug, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- Correspondence: (J.C.); (J.H.)
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; (L.H.); (C.S.); (T.L.); (X.S.); (J.L.); (S.G.); (R.Z.); (Z.A.)
- Center for Imaging and Systems Biology, School of Pharmacy, Minzu University of China, Beijing 100081, China
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23
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Jiang H, Zhang Y, Liu Z, Wang X, He J, Jin H. Advanced applications of mass spectrometry imaging technology in quality control and safety assessments of traditional Chinese medicines. JOURNAL OF ETHNOPHARMACOLOGY 2022; 284:114760. [PMID: 34678417 PMCID: PMC9715987 DOI: 10.1016/j.jep.2021.114760] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 10/05/2021] [Accepted: 10/18/2021] [Indexed: 05/13/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Traditional Chinese medicines (TCMs) have made great contributions to the prevention and treatment of human diseases in China, and especially in cases of COVID-19. However, due to quality problems, the lack of standards, and the diversity of dosage forms, adverse reactions to TCMs often occur. Moreover, the composition of TCMs makes them extremely challenging to extract and isolate, complicating studies of toxicity mechanisms. AIM OF THE REVIEW The aim of this paper is therefore to summarize the advanced applications of mass spectrometry imaging (MSI) technology in the quality control, safety evaluations, and determination of toxicity mechanisms of TCMs. MATERIALS AND METHODS Relevant studies from the literature have been collected from scientific databases, such as "PubMed", "Scifinder", "Elsevier", "Google Scholar" using the keywords "MSI", "traditional Chinese medicines", "quality control", "metabolomics", and "mechanism". RESULTS MSI is a new analytical imaging technology that can detect and image the metabolic changes of multiple components of TCMs in plants and animals in a high throughput manner. Compared to other chemical analysis methods, such as liquid chromatography-mass spectrometry (LC-MS), this method does not require the complex extraction and separation of TCMs, and is fast, has high sensitivity, is label-free, and can be performed in high-throughput. Combined with chemometrics methods, MSI can be quickly and easily used for quality screening of TCMs. In addition, this technology can be used to further focus on potential biomarkers and explore the therapeutic/toxic mechanisms of TCMs. CONCLUSIONS As a new type of analysis method, MSI has unique advantages to metabolic analysis, quality control, and mechanisms of action explorations of TCMs, and contributes to the establishment of quality standards to explore the safety and toxicology of TCMs.
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Affiliation(s)
- Haiyan Jiang
- New Drug Safety Evaluation Center, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Yaxin Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Zhigang Liu
- School of Biological Science and Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Xiangyi Wang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China; NMPA Key Laboratory for Safety Research and Evaluation of Innovative Drug, Beijing 100050, China.
| | - Hongtao Jin
- New Drug Safety Evaluation Center, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China; Beijing Union-Genius Pharmaceutical Technology Development Co., Ltd., Beijing 100176, China; NMPA Key Laboratory for Safety Research and Evaluation of Innovative Drug, Beijing 100050, China.
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24
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Hou Y, Gao Y, Guo S, Zhang Z, Chen R, Zhang X. Applications of spatially resolved omics in the field of endocrine tumors. Front Endocrinol (Lausanne) 2022; 13:993081. [PMID: 36704039 PMCID: PMC9873308 DOI: 10.3389/fendo.2022.993081] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 12/15/2022] [Indexed: 01/11/2023] Open
Abstract
Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors.
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Affiliation(s)
- Yinuo Hou
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
| | - Yan Gao
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
| | - Shudi Guo
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
| | - Zhibin Zhang
- General Surgery, Tianjin First Center Hospital, Tianjin, China
- *Correspondence: Zhibin Zhang, ; Ruibing Chen, ; Xiangyang Zhang,
| | - Ruibing Chen
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
- *Correspondence: Zhibin Zhang, ; Ruibing Chen, ; Xiangyang Zhang,
| | - Xiangyang Zhang
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
- *Correspondence: Zhibin Zhang, ; Ruibing Chen, ; Xiangyang Zhang,
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25
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Luo Z, Wang W, Pang X, Zhang J, Sun C, Zhou X, He J, Zhang R, Li X, Lian Z, Abliz Z. Writing sequence identification of seals and signatures in documents using ambient mass spectrometry imaging with chemometric methods. Talanta 2021; 235:122804. [PMID: 34517662 DOI: 10.1016/j.talanta.2021.122804] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 08/12/2021] [Accepted: 08/13/2021] [Indexed: 10/20/2022]
Abstract
Identifying the writing sequence of seals and signatures in documents is often performed and difficult to resolve in forensic determination. Morphological and physical-chemical analysis methods are often limited by the destructive nature of samples, a high signal response strength and specific materials. Mass spectrometry imaging (MSI) has been used as an alternative method because it can generate molecular images from many surfaces and produce rich chemical information. Herein, we developed a sequence identification method by coupling an air flow-assisted desorption electrospray ionization (AFADESI)-MSI system with a chemometric analysis, which can holistically and directly analyse document samples under ambient, moderate and selectable conditions and maintain the original appearance of the paper documents after sampling. By integrating principal component analysis (PCA) and the partial least squares discriminant analysis (PLS-DA), equivocal point analysis can be objectively performed, where knowing the components of the seal or signature is not necessary to identify the sequence. In total, 28 prepared samples with known sequences and two original blind test samples were analysed. One prepared sample was analysed in negative ionization mode, and other samples were inferred in positive ionization mode. All writing sequences were in accordance with the actual case. The writing sequence of the blind testing of the original samples was correctly identified. This study provided a convenient, objective and quasi-nondestructive method to investigate the sequence differences among equivocal document samples and is promising for providing an alternative method for the sequence identification of seals and signatures in questionable documents.
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Affiliation(s)
- Zhigang Luo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Weixin Wang
- Institute of Forensic Science, Ministry of Public Security, Beijing, 100038, PR China
| | - Xuechao Pang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Jin Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Chenglong Sun
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Xia Zhou
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Xin Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Zhe Lian
- Institute of Forensic Science, Ministry of Public Security, Beijing, 100038, PR China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China; Center for Imaging & Systems Biology, Minzu University of China, Beijing, 100081, PR China.
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26
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Innovation in drug toxicology: Application of mass spectrometry imaging technology. Toxicology 2021; 464:153000. [PMID: 34695509 DOI: 10.1016/j.tox.2021.153000] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 09/21/2021] [Accepted: 10/18/2021] [Indexed: 01/19/2023]
Abstract
Mass spectrometry imaging (MSI) is a powerful molecular imaging technology that can obtain qualitative, quantitative, and location information by simultaneously detecting and mapping endogenous or exogenous molecules in biological tissue slices without specific chemical labeling or complex sample pretreatment. This article reviews the progress made in MSI and its application in drug toxicology research, including the tissue distribution of toxic drugs and their metabolites, the target organs (liver, kidney, lung, eye, and central nervous system) of toxic drugs, the discovery of toxicity-associated biomarkers, and explanations of the mechanisms of drug toxicity when MSI is combined with the cutting-edge omics methodologies. The unique advantages and broad prospects of this technology have been fully demonstrated to further promote its wider use in the field of pharmaceutical toxicology.
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27
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Yang X, Song X, Zhang X, Shankar V, Wang S, Yang Y, Chen S, Zhang L, Ni Y, Zare RN, Hu Q. In situ DESI-MSI lipidomic profiles of mucosal margin of oral squamous cell carcinoma. EBioMedicine 2021; 70:103529. [PMID: 34391097 PMCID: PMC8374374 DOI: 10.1016/j.ebiom.2021.103529] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Revised: 07/15/2021] [Accepted: 07/28/2021] [Indexed: 01/22/2023] Open
Abstract
Background Although there is consensus that the optimal safe margin is ≥ 5mm, obtaining clear margins (≥5 mm) intraoperatively seems to be the major challenge. We applied a molecular diagnostic method at the lipidomic level to determine the safe surgical resection margin of OSCC by desorption electrospray ionisation mass spectrometry imaging (DESI-MSI). Methods By overlaying mass spectrometry images with hematoxylin-eosin staining (H&E) from 18 recruited OSCC participants, the mass spectra of all pixels across the diagnosed tumour and continuous mucosal margin regions were extracted to serve as the training and validation datasets. A Lasso regression model was used to evaluate the test performance. Findings By leave-one-out validation, the Lasso model achieved 88.6% accuracy in distinguishing between tumour and normal regions. To determine the safe surgical resection distance and margin status of OSCC, a set of 14 lipid ions that gradually decreased from tumour to normal tissue was assigned higher weight coefficients in the Lasso model. The safe surgical resection distance of OSCC was measured using the developed 14 lipid ion molecular diagnostic model for clinical reference. The overall accuracy of predicting tumours, positive margins, and negative margins was 92.6%. Interpretation The spatial segmentation results based on our diagnostic model not only clearly delineated the tumour and normal tissue, but also distinguished the different status of surgical margins. Meanwhile, the safe surgical resection margin of OSCC on frozen sections can also be accurately measured using the developed diagnostic model. Funding This study was supported by Nanjing Municipal Key Medical Laboratory Constructional Project Funding (since 2016) and the Centre of Nanjing Clinical Medicine Tumour (since 2014).
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Affiliation(s)
- Xihu Yang
- Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, 210008, China; Department of Oral and Maxillofacial Surgery, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210000, China.
| | - Xiaowei Song
- Department of Chemistry, Fudan University, Shanghai, 200438, China
| | - Xiaoxin Zhang
- Central Laboratory of Stomatology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210000, China
| | - Vishnu Shankar
- Department of Chemistry, Stanford University, Stanford, California, 94305, USA
| | - Shuai Wang
- Department of Oral and Maxillofacial Surgery, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210000, China
| | - Yan Yang
- Department of Oral Pathology, Stomatological hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210000, China
| | - Sheng Chen
- Department of Oral Pathology, Stomatological hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210000, China
| | - Lei Zhang
- Department of Oral Pathology, Stomatological hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210000, China
| | - Yanhong Ni
- Central Laboratory of Stomatology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210000, China.
| | - Richard N Zare
- Department of Chemistry, Fudan University, Shanghai, 200438, China; Department of Chemistry, Stanford University, Stanford, California, 94305, USA.
| | - Qingang Hu
- Department of Oral and Maxillofacial Surgery, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210000, China.
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28
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Song X, Zang Q, Zare RN. Hydrogen-Deuterium Exchange Desorption Electrospray Ionization Mass Spectrometry Visualizes an Acidic Tumor Microenvironment. Anal Chem 2021; 93:10411-10417. [PMID: 34279072 DOI: 10.1021/acs.analchem.1c02026] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
We report that microdroplet hydrogen-deuterium exchange (HDX) detected by desorption electrospray ionization mass spectrometry imaging (DESI-MSI) allows the measurement of the acidity of a tissue sample. The integration of HDX and DESI-MSI has been applied to visualize the acidic tumor microenvironment (TME). HDX-DESI-MSI enables the simultaneous collection of regional pH variation and its corresponding in-depth metabolomic changes. This technique is a cost-effective tool for providing insight into the pH-dependent tumor metabolism heterogeneity.
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Affiliation(s)
- Xiaowei Song
- Stanford University, Department of Chemistry, Stanford, California 94305, United States.,Department of Chemistry, Fudan University, Shanghai 200438, China
| | - Qingce Zang
- Institute of Materia Medica, Chinese Academy of Medical Science, Peking Union Medical College, Beijing 100050, China
| | - Richard N Zare
- Stanford University, Department of Chemistry, Stanford, California 94305, United States
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29
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Li C, Li K, Xu X, Qi W, Hu X, Jin P. A pilot study for colorectal carcinoma screening by instant metabolomic profiles using conductive polymer spray ionization mass spectrometry. Biochim Biophys Acta Mol Basis Dis 2021; 1867:166210. [PMID: 34246751 DOI: 10.1016/j.bbadis.2021.166210] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 06/17/2021] [Accepted: 07/06/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND The rapid and accurate discrimination of colorectal carcinoma (CRC) and polyps at the molecular level enables early intervention of CRC, which can greatly improve the 5-year survival rate of patients. Here we reported the potential of conductive polymer spray ionization mass spectrometry (CPSI-MS) in successfully screening CRC according to the serum metabolic profile. METHODS Trace intravenous blood (50 μL) was collected from 60 colorectal carcinoma (CRC) and 60 polyp patients, respectively. After centrifugation, serum (2 μL) was loaded onto the tip of conductive polymer to form a dried serum spot. When the 5 μL methanol-water (1:1, v/v) extraction solvent was spiked onto the dried serum spot followed with +4.5 kV high voltage applied on the polymer tip, the extracted components will be ionized and carried into the MS system for direct metabolic profiling. FINDINGS There were 51 metabolites discovered to be significantly changed in CRC serum compared to polyps. Combining these metabolites as the characteristic panel, the ideal diagnostic performance was achieved by Lasso regression model with the accuracy of 88.3%. INTERPRETATION This pilot study demonstrated the potential of CPSI-MS as a cost-effective tool in large-scale CRC screening in the high-risk population.
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Affiliation(s)
- Chao Li
- Department of Pharmacy, Beijing Hospital, Beijing 100730, China; National Center of Gerontology, Beijing 100730, China; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; Beijing Key Laboratory of Assessment of Clinical Drugs Risk and Individual Application (Beijing Hospital), Beijing 100730, China
| | - Kexin Li
- National Center of Gerontology, Beijing 100730, China; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; Clinical Trial Center, Beijing Hospital, Beijing 100730, China
| | - Xiaoyu Xu
- National Center of Gerontology, Beijing 100730, China; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; Clinical Trial Center, Beijing Hospital, Beijing 100730, China
| | - Wenyuan Qi
- National Center of Gerontology, Beijing 100730, China; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; Clinical Trial Center, Beijing Hospital, Beijing 100730, China
| | - Xin Hu
- Department of Pharmacy, Beijing Hospital, Beijing 100730, China; National Center of Gerontology, Beijing 100730, China; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; Beijing Key Laboratory of Assessment of Clinical Drugs Risk and Individual Application (Beijing Hospital), Beijing 100730, China
| | - Pengfei Jin
- Department of Pharmacy, Beijing Hospital, Beijing 100730, China; National Center of Gerontology, Beijing 100730, China; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; Beijing Key Laboratory of Assessment of Clinical Drugs Risk and Individual Application (Beijing Hospital), Beijing 100730, China.
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30
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Pang X, Gao S, Ga M, Zhang J, Luo Z, Chen Y, Zhang R, He J, Abliz Z. Mapping Metabolic Networks in the Brain by Ambient Mass Spectrometry Imaging and Metabolomics. Anal Chem 2021; 93:6746-6754. [PMID: 33890766 DOI: 10.1021/acs.analchem.1c00467] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Metabolic networks and their dysfunction in the brain are closely associated with central nervous function and many psychogenic diseases. Thus, it is of utmost importance to develop a high-throughput imaging method for metabolic network mapping. Here, we developed a metabolic network mapping method to discover the metabolic contexts and alterations with spatially resolved information from the microregion of the brain by ambient-air flow-assisted desorption electrospray ionization mass spectrometry imaging and metabolomics analysis, which can be performed without any chemical derivatization, labels, or complex sample pretreatment. This method can map hundreds of different polar functional metabolites involved in multiple metabolic pathways, including not only neurotransmitters but also purines, organic acids, polyamines, cholines, and carbohydrates, in the rat brain. These high-coverage metabolite profile and microregional distribution information constitute complex networks that regulate advanced functions in the central nervous system. Moreover, this methodology was further used to discover not only the dysregulated metabolites but also the brain microregions involved in the pathology of a scopolamine-treated Alzheimer's model. Furthermore, this methodology was demonstrated to be a powerful visualizing tool that could offer novel insight into the metabolic events and provide spatial information about these events in central nervous system diseases.
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Affiliation(s)
- Xuechao Pang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Shanshan Gao
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Man Ga
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jin Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Zhigang Luo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Yanhua Chen
- Centre for Imaging & Systems Biology, Minzu University of China, Beijing 100081, China.,Key Laboratory of Ethnomedicine of Ministry of Education, School of Pharmacy, Minzu University of China, Beijing 100081, China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.,Centre for Imaging & Systems Biology, Minzu University of China, Beijing 100081, China.,Key Laboratory of Ethnomedicine of Ministry of Education, School of Pharmacy, Minzu University of China, Beijing 100081, China
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31
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Li N, Nie H, Jiang L, Ruan G, Du F, Liu H. Recent advances of ambient ionization mass spectrometry imaging in clinical research. J Sep Sci 2020; 43:3146-3163. [PMID: 32573988 DOI: 10.1002/jssc.202000273] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 05/03/2020] [Accepted: 05/06/2020] [Indexed: 02/06/2023]
Abstract
The structural information and spatial distribution of molecules in biological tissues are closely related to the potential molecular mechanisms of disease origin, transfer, and classification. Ambient ionization mass spectrometry imaging is an effective tool that provides molecular images while describing in situ information of biomolecules in complex samples, in which ionization occurs at atmospheric pressure with the samples being analyzed in the native state. Ambient ionization mass spectrometry imaging can directly analyze tissue samples at a fairly high resolution to obtain molecules in situ information on the tissue surface to identify pathological features associated with a disease, resulting in the wide applications in pharmacy, food science, botanical research, and especially clinical research. Herein, novel ambient ionization techniques, such as techniques based on spray and solid-liquid extraction, techniques based on plasma desorption, techniques based on laser desorption ablation, and techniques based on acoustic desorption were introduced, and the data processing of ambient ionization mass spectrometry imaging was briefly reviewed. Besides, we also highlight recent applications of this imaging technology in clinical researches and discuss the challenges in this imaging technology and the perspectives on the future of the clinical research.
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Affiliation(s)
- Na Li
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
- College of Chemistry and Molecular Engineering, Peking University, Beijing, P. R. China
| | - Honggang Nie
- College of Chemistry and Molecular Engineering, Peking University, Beijing, P. R. China
| | - Liping Jiang
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
| | - Guihua Ruan
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
| | - Fuyou Du
- Guangxi Key Laboratory of Electrochemical and Magnetochemical Functional Materials, College of Chemistry and Bioengineering, Guilin University of Technology, Guilin, P. R. China
- College of Biological and Environmental Engineering, Changsha University, Changsha, P. R. China
| | - Huwei Liu
- College of Chemistry and Molecular Engineering, Peking University, Beijing, P. R. China
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32
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Recent advances of ambient mass spectrometry imaging for biological tissues: A review. Anal Chim Acta 2020; 1117:74-88. [DOI: 10.1016/j.aca.2020.01.052] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 01/21/2020] [Accepted: 01/22/2020] [Indexed: 12/30/2022]
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33
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Yee WLS, Drum CL. Increasing Complexity to Simplify Clinical Care: High Resolution Mass Spectrometry as an Enabler of AI Guided Clinical and Therapeutic Monitoring. ADVANCED THERAPEUTICS 2020. [DOI: 10.1002/adtp.201900163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Wei Loong Sherman Yee
- Yong Loo Lin School of MedicineDepartment of MedicineNational University of Singapore Singapore 119077 Singapore
- Cardiovascular Research Institute (CVRI)National University Health System Singapore 119228 Singapore
| | - Chester Lee Drum
- Yong Loo Lin School of MedicineDepartment of MedicineNational University of Singapore Singapore 119077 Singapore
- Cardiovascular Research Institute (CVRI)National University Health System Singapore 119228 Singapore
- Yong Loo Lin School of MedicineDepartment of BiochemistryNational University of Singapore Singapore 119077 Singapore
- The N.1 Institute for Health (N.1)National University of Singapore Singapore 119077 Singapore
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34
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Tortorella S, Tiberi P, Bowman AP, Claes BSR, Ščupáková K, Heeren RMA, Ellis SR, Cruciani G. LipostarMSI: Comprehensive, Vendor-Neutral Software for Visualization, Data Analysis, and Automated Molecular Identification in Mass Spectrometry Imaging. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2020; 31:155-163. [PMID: 32881505 DOI: 10.1021/jasms.9b00034] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Mass Spectrometry Imaging (MSI) is an established and powerful MS technique that enables molecular mapping of tissues and cells finding widespread applications in academic, medical, and pharmaceutical industries. As both the applications and MSI technology have undergone rapid growth and improvement, the challenges associated both with analyzing large datasets and identifying the many detected molecular species have become apparent. The lack of readily available and comprehensive software covering all necessary data analysis steps has further compounded this challenge. To address this issue we developed LipostarMSI, comprehensive and vendor-neutral software for targeted and untargeted MSI data analysis. Through user-friendly implementation of image visualization and co-registration, univariate and multivariate image and spectral analysis, and for the first time, advanced lipid, metabolite, and drug metabolite (MetID) automated identification, LipostarMSI effectively streamlines biochemical interpretation of the data. Here, we introduce LipostarMSI and case studies demonstrating the versatility and many capabilities of the software.
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Affiliation(s)
- Sara Tortorella
- Molecular Horizon Srl, Via Montelino 30, 06084 Bettona, Perugia, Italy
- Consortium for Computational Molecular and Materials Sciences (CMS)2, Via Elce di Sotto 8, 06123 Perugia, Italy
| | - Paolo Tiberi
- Molecular Discovery Ltd., Centennial Park, WD6 3FG Borehamwood, Hertfordshire, United Kingdom
| | - Andrew P Bowman
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
| | - Britt S R Claes
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
| | - Klára Ščupáková
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
| | - Ron M A Heeren
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
| | - Shane R Ellis
- Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
| | - Gabriele Cruciani
- Consortium for Computational Molecular and Materials Sciences (CMS)2, Via Elce di Sotto 8, 06123 Perugia, Italy
- Department of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, 06123 Perugia, Italy
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35
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Chemical Analysis and Imaging of Fingerprints by Air-flow Assisted Desorption Electrospray Ionization Mass Spectrometry. CHINESE JOURNAL OF ANALYTICAL CHEMISTRY 2019. [DOI: 10.1016/s1872-2040(19)61205-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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36
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Pérez-Guaita D, Quintás G, Kuligowski J. Discriminant analysis and feature selection in mass spectrometry imaging using constrained repeated random sampling - Cross validation (CORRS-CV). Anal Chim Acta 2019; 1097:30-36. [PMID: 31910967 DOI: 10.1016/j.aca.2019.10.039] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 10/16/2019] [Accepted: 10/18/2019] [Indexed: 12/20/2022]
Abstract
The identification of biomarkers through Mass spectrometry imaging (MSI) is gaining popularity in the clinical field. However, considering the complexity of spectral and spatial variables faced, data mining of the hyperspectral images can be troublesome. The discovery of markers generally depends on the creation of classification models which should be validated to ensure the statistical significance of the discriminants m/z detected. Internal validation using resampling methods such as cross validation (CV) are widely used for model selection, the estimation of its generalization performance and biomarker discovery when sample sizes are limited and an independent test set is not available. Here, we introduce for first time the use of Constrained Repeated Random Subsampling CV (CORRS-CV) on multi-images for the validation of classification models on MSI. Although several aspects must be taken into account (e.g. image size, CORRS-CV∂value, the similarity across spatially close pixels, the total computation time), CORRS-CV provides more accurate estimates of the model performance than k-fold CV using of biological replicates to define the data split when the number of biological replicates is scarce and holding images back for testing is a waste of valuable information. Besides, the combined use of CORRS-CV and rank products increases the robustness of the selection of discriminant features as candidate biomarkers which is an important issue due to the increased biological, environmental and technical variabilities when analysing multiple images, especially from human tissues collected in clinical studies.
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Affiliation(s)
| | - Guillermo Quintás
- Health & Biomedicine, LEITAT Technological Center, Barcelona, Spain; Unidad Analítica, Health Research Institute Hospital La Fe, Valencia, Spain.
| | - Julia Kuligowski
- Neonatal Research Unit, Health Research Institute Hospital La Fe, Valencia, Spain
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37
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Huang L, Mao X, Sun C, Luo Z, Song X, Li X, Zhang R, Lv Y, Chen J, He J, Abliz Z. A graphical data processing pipeline for mass spectrometry imaging-based spatially resolved metabolomics on tumor heterogeneity. Anal Chim Acta 2019; 1077:183-190. [DOI: 10.1016/j.aca.2019.05.068] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2019] [Revised: 05/26/2019] [Accepted: 05/28/2019] [Indexed: 10/26/2022]
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38
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Song X, He J, Li C, Sun C, Pang X, Zhang J, Zang Q, Luo Z, Li X, Zhang R, Abliz Z. Fabrication of homogenous three-dimensional biomimetic tissue for mass spectrometry imaging. JOURNAL OF MASS SPECTROMETRY : JMS 2019; 54:378-388. [PMID: 30742348 DOI: 10.1002/jms.4342] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2018] [Revised: 01/26/2019] [Accepted: 02/06/2019] [Indexed: 06/09/2023]
Abstract
Reference samples are essential for mass spectrometric method optimization, data quality control, and target analyte quantitation. However, it is highly challenging to prepare an ideal homogeneous, standard-spiked tissue sample for mass spectrometry imaging (MSI) research. Herein, we present a standard-spiked 3D biomimetic tissue model fabricated with native cells, homogenate matrix, and biocompatible polymer. Unlike traditional homogenized tissue surrogates or those constructed with "on-tissue" or "under-tissue" micropipetting strategies, this simulated tissue shares both structural integrity of cells and homogeneous properties of matrix. As a result, analyte standards could undergo more in-depth incorporation and has a more comparable native status with a real tissue. Series of tissue sections made from the 3D tissue model were proven to be feasible and useful for the parameter optimization, analyte quantitation, and calibration curve fitting for the air-flow assisted desorption electrospray ionization MSI. Additionally, by analyzing the quality control model sections, we proposed a median principal component score calibration and demonstrated that this method can normalize instrumental fluctuations to stable levels in a large-scale untargeted MSI experiments for the reliable metabolomic biomarker discovery. Thus, these results indicated that the standard-spiked 3D biomimetic tissue has convincing significance in MSI analysis.
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Affiliation(s)
- Xiaowei Song
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Chao Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Chenglong Sun
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Xuechao Pang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Jin Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Qingce Zang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Zhigang Luo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Xin Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China
- Centre for Imaging and Systems Biology, School of Pharmacy, Minzu University of China, Beijing, 100081, China
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39
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Luo Z, Liu D, Pang X, Yang W, He J, Zhang R, Zhu C, Chen Y, Li X, Zhang J, Shi J, Abliz Z. Whole-body spatially-resolved metabolomics method for profiling the metabolic differences of epimer drug candidates using ambient mass spectrometry imaging. Talanta 2019; 202:198-206. [PMID: 31171170 DOI: 10.1016/j.talanta.2019.04.068] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 04/04/2019] [Accepted: 04/27/2019] [Indexed: 12/29/2022]
Abstract
Investigation of the in vivo drug action and metabolic differences of epimer drugs is challenging. Whole-body MSI analysis can visually present the stereoscopic distribution of molecules related to the interaction of drugs and organisms, and can provide more comprehensive organ-specific profiling information. Herein, we developed a whole-body spatially-resolved imaging metabolomics method based on an air flow-assisted ionisation desorption electrospray ionisation (AFADESI)-MSI system coupled with a high-resolution mass spectrometer and highly discriminating imaging software. The epimeric sedative-hypnotic drug candidates YZG-331 and YZG-330 were selected as examples, and rats administered normal or high oral doses were used. By performing multivariate statistical data-mining on the combined MSI data, organ-specific differential ions were screened. By comparing the variations in the relative contents of the drugs, their metabolites, and endogenous neurotransmitters throughout whole-body tissue sections of the rats, rich information that could potentially explain the more significant sedative-hypnotic effects of YZG-330 compared to YZG-331 was obtained. Such as the increased ratio of gamma-aminobutyric acid in the brain and stomach of the rats (0.25, 0.47, 0.68, 0.30, and 0.89 for the control and YZG-331-H, YZG-330-H, YZG-331-L, and YZG-330-L, respectively) were interesting. This study provided a convenient and visual method to investigate in vivo molecular metabolic differences and provide insight towards a better understanding of the pharmacodynamic mechanisms of these sedative-hypnotic drug-candidates.
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Affiliation(s)
- Zhigang Luo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Dan Liu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Xuechao Pang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Wanqi Yang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Chenggen Zhu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Yanhua Chen
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Xin Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Jianjun Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Jiangong Shi
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, PR China; Center for Imaging and Systems Biology, School of Pharmacy, Minzu University of China, Beijing, 100081, PR China.
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40
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Weiskirchen R, Weiskirchen S, Kim P, Winkler R. Software solutions for evaluation and visualization of laser ablation inductively coupled plasma mass spectrometry imaging (LA-ICP-MSI) data: a short overview. J Cheminform 2019; 11:16. [PMID: 30778692 PMCID: PMC6690067 DOI: 10.1186/s13321-019-0338-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 02/09/2019] [Indexed: 12/19/2022] Open
Abstract
Mass spectrometry imaging (MSI) using laser ablation (LA) inductively coupled plasma (ICP) is an innovative and exciting methodology to perform highly sensitive elemental analyses. LA-ICP-MSI of metals, trace elements or isotopes in tissues has been applied to a range of biological samples. Several LA-ICP-MSI studies have shown that metals have a highly compartmentalized distribution in some organs, which might be altered in consequence of genetic diseases, intoxication, or malnutrition. Although metal imaging by LA-ICP-MSI is an established methodology, potential pitfalls in the determination of metal concentrations might result from erroneous calibration, standardization, and normalization. In addition, for simple display of final imaging results, most LA-ICP-MSI users prefer to process their measurements by commercial processing software. Such programs typically visualize the regional metal differences in colorful and vivid imaging maps, but might not represent the actual signal densities correctly. There is a great abundance of such MSI data processing programs available differing in quality, usability, integrated features, workflow, reliability, system requirements, speed of data processing, and price. Some software packages contain a multitude of features which are superfluous for most users. In contrast, often only few data formats are used, in case of commercial programs even only the instrument provider’s own raw data format. Therefore, first time and average users are often confused and helpless in choosing the correct software for processing their data. Here we have briefly summarized software packages, data routines, macros, programming tools, scripts, algorithms, or self-written patches and updates for existing programs presently in use for mining LA-ICP-MSI data.![]()
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Affiliation(s)
- Ralf Weiskirchen
- Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry (IFMPEGKC), RWTH University Hospital Aachen, 52074, Aachen, Germany.
| | - Sabine Weiskirchen
- Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry (IFMPEGKC), RWTH University Hospital Aachen, 52074, Aachen, Germany
| | - Philipp Kim
- Institute of Molecular Pathobiochemistry, Experimental Gene Therapy and Clinical Chemistry (IFMPEGKC), RWTH University Hospital Aachen, 52074, Aachen, Germany
| | - Robert Winkler
- Department of Biochemistry and Biotechnology, Center for Research and Advanced Studies (CINVESTAV) Irapuato, Km. 9.6 Libramiento Norte Carr. Irapuato-León, 36824, Irapuato, Gto., Mexico. .,Mass Spectrometry Group, Max Planck Institute for Chemical Ecology, Hans-Knöll-Straße 8, 07745, Jena, Germany.
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Song X, He J, Pang X, Zhang J, Sun C, Huang L, Li C, Zang Q, Li X, Luo Z, Zhang R, Xie P, Liu X, Li Y, Chen X, Abliz Z. Virtual Calibration Quantitative Mass Spectrometry Imaging for Accurately Mapping Analytes across Heterogenous Biotissue. Anal Chem 2019; 91:2838-2846. [PMID: 30636407 DOI: 10.1021/acs.analchem.8b04762] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
It is highly challenging to quantitatively map multiple analytes in biotissues without specific chemical labeling. Quantitative mass spectrometry imaging (QMSI) has this potential but still poses technical issues for its variant ionization efficiency across a complicated, heterogeneous biomatrices. Herein, a self-developed air-flow-assisted desorption electrospray ionization (AFADESI) is introduced to present a proof of concept method, virtual calibration (VC) QMSI. This method screens and utilizes analyte response-related endogenous metabolite ions from each mass spectrum as native internal standards (IS). Through machine-learning-based regression and clustering, tissue-specific ionization variation can be automatically recognized, predicted, and normalized region by region or pixel by pixel. Therefore, the quantity of analytes can be accurately mapped across highly structural biosamples including whole body, kidney, brain, tumor, etc. VC-QMSI has the advantages of simple sample preparation without laborious isotopic IS synthesis, extrapolation for those unknown tissues or regions without previous investigation, and automatic spatial recognition without histological guidance. This strategy is suitable for mass spectrometry imaging using a variety of in situ ionization techniques. It is believed that VC-QMSI has wide applicability for drug candidate's discovery, molecular mechanism elucidation, biomarker validation, and clinical diagnosis.
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Affiliation(s)
- Xiaowei Song
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Xuechao Pang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Jin Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Chenglong Sun
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Luojiao Huang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Chao Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Qingce Zang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Xin Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Zhigang Luo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Ping Xie
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Xiaoyu Liu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Yan Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Xiaoguang Chen
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050 , People's Republic of China.,Centre for Imaging and Systems Biology, School of Pharmacy , Minzu University of China , Beijing 100081 , People's Republic of China
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Abstract
Tumor cells reprogram their metabolism to support cell growth, proliferation, and differentiation, thus driving cancer progression. Profiling of the metabolic signatures in heterogeneous tumors facilitates the understanding of tumor metabolism and introduces potential metabolic vulnerabilities that might be targeted therapeutically. We proposed a spatially resolved metabolomics method for high-throughput discovery of tumor-associated metabolite and enzyme alterations using ambient mass spectrometry imaging. Metabolic pathway-related metabolites and metabolic enzymes that are associated with tumor metabolism were efficiently discovered and visualized in heterogeneous esophageal cancer tissues. Spatially resolved metabolic alterations hold the key to defining the dependencies of metabolism that are most limiting for cancer growth and exploring metabolic targeted strategies for better cancer treatment. Characterization of tumor metabolism with spatial information contributes to our understanding of complex cancer metabolic reprogramming, facilitating the discovery of potential metabolic vulnerabilities that might be targeted for tumor therapy. However, given the metabolic variability and flexibility of tumors, it is still challenging to characterize global metabolic alterations in heterogeneous cancer. Here, we propose a spatially resolved metabolomics approach to discover tumor-associated metabolites and metabolic enzymes directly in their native state. A variety of metabolites localized in different metabolic pathways were mapped by airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) in tissues from 256 esophageal cancer patients. In combination with in situ metabolomics analysis, this method provided clues into tumor-associated metabolic pathways, including proline biosynthesis, glutamine metabolism, uridine metabolism, histidine metabolism, fatty acid biosynthesis, and polyamine biosynthesis. Six abnormally expressed metabolic enzymes that are closely associated with the altered metabolic pathways were further discovered in esophageal squamous cell carcinoma (ESCC). Notably, pyrroline-5-carboxylate reductase 2 (PYCR2) and uridine phosphorylase 1 (UPase1) were found to be altered in ESCC. The spatially resolved metabolomics reveal what occurs in cancer at the molecular level, from metabolites to enzymes, and thus provide insights into the understanding of cancer metabolic reprogramming.
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Misra BB, Mohapatra S. Tools and resources for metabolomics research community: A 2017-2018 update. Electrophoresis 2018; 40:227-246. [PMID: 30443919 DOI: 10.1002/elps.201800428] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 11/09/2018] [Accepted: 11/09/2018] [Indexed: 01/09/2023]
Abstract
The scale at which MS- and NMR-based platforms generate metabolomics datasets for both research, core, and clinical facilities to address challenges in the various sciences-ranging from biomedical to agricultural-is underappreciated. Thus, metabolomics efforts spanning microbe, environment, plant, animal, and human systems have led to continual and concomitant growth of in silico resources for analysis and interpretation of these datasets. These software tools, resources, and databases drive the field forward to help keep pace with the amount of data being generated and the sophisticated and diverse analytical platforms that are being used to generate these metabolomics datasets. To address challenges in data preprocessing, metabolite annotation, statistical interrogation, visualization, interpretation, and integration, the metabolomics and informatics research community comes up with hundreds of tools every year. The purpose of the present review is to provide a brief and useful summary of more than 95 metabolomics tools, software, and databases that were either developed or significantly improved during 2017-2018. We hope to see this review help readers, developers, and researchers to obtain informed access to these thorough lists of resources for further improvisation, implementation, and application in due course of time.
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Affiliation(s)
- Biswapriya B Misra
- Department of Internal Medicine, Section of Molecular Medicine, Medical Center Boulevard, Winston-Salem, NC, USA
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