1
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Wang X, Peng R, Zhao L. Multiscale metabolomics techniques: Insights into neuroscience research. Neurobiol Dis 2024; 198:106541. [PMID: 38806132 DOI: 10.1016/j.nbd.2024.106541] [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: 04/10/2024] [Revised: 05/21/2024] [Accepted: 05/23/2024] [Indexed: 05/30/2024] Open
Abstract
The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.
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Affiliation(s)
- Xiaoya Wang
- Beijing Institute of Radiation Medicine, Beijing 100850, China
| | - Ruiyun Peng
- Beijing Institute of Radiation Medicine, Beijing 100850, China.
| | - Li Zhao
- Beijing Institute of Radiation Medicine, Beijing 100850, China.
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2
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Sun F, Li H, Sun D, Fu S, Gu L, Shao X, Wang Q, Dong X, Duan B, Xing F, Wu J, Xiao M, Zhao F, Han JDJ, Liu Q, Fan X, Li C, Wang C, Shi T. Single-cell omics: experimental workflow, data analyses and applications. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-023-2561-0. [PMID: 39060615 DOI: 10.1007/s11427-023-2561-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/18/2024] [Indexed: 07/28/2024]
Abstract
Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
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Affiliation(s)
- Fengying Sun
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China
| | - Haoyan Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Dongqing Sun
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Shaliu Fu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Lei Gu
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Shao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China
| | - Qinqin Wang
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Dong
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Bin Duan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Feiyang Xing
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Jun Wu
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Minmin Xiao
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Qi Liu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China.
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China.
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China.
- Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
| | - Chen Li
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Chenfei Wang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Tieliu Shi
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
- Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai, 200062, China.
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3
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Ma X, Fernández FM. Advances in mass spectrometry imaging for spatial cancer metabolomics. MASS SPECTROMETRY REVIEWS 2024; 43:235-268. [PMID: 36065601 PMCID: PMC9986357 DOI: 10.1002/mas.21804] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/02/2022] [Accepted: 08/02/2022] [Indexed: 05/09/2023]
Abstract
Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.
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Affiliation(s)
- Xin Ma
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Facundo M Fernández
- School of Chemistry and Biochemistry and Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
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4
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Lan Y, Chen X, Yang Z. Quantification of Nitric Oxide in Single Cells Using the Single-Probe Mass Spectrometry Technique. Anal Chem 2023; 95:18871-18879. [PMID: 38092461 DOI: 10.1021/acs.analchem.3c04393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Nitric oxide (NO) is a small molecule that plays important roles in biological systems and human diseases. The abundance of intracellular NO is tightly related to numerous biological processes. Due to cell heterogeneity, the intracellular NO amounts significantly vary from cell to cell, and therefore, any meaningful studies need to be conducted at the single-cell level. However, measuring NO in single cells is very challenging, primarily due to the extremely small size of single cells and reactive nature of NO. In the current studies, the quantitative reaction between NO and amlodipine, a compound containing the Hantzsch ester group, was performed in live cells. The product dehydro amlodipine was then detected by the Single-probe single-cell mass spectrometry technique to quantify NO in single cells. The experimental results indicated heterogeneous distributions of intracellular NO amounts in single cells with the existence of subpopulations.
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Affiliation(s)
- Yunpeng Lan
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Xingxiu Chen
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
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5
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Jia F, Zhao X, Zhao Y. Advancements in ToF-SIMS imaging for life sciences. Front Chem 2023; 11:1237408. [PMID: 37693171 PMCID: PMC10483116 DOI: 10.3389/fchem.2023.1237408] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/14/2023] [Indexed: 09/12/2023] Open
Abstract
In the last 2 decades, Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) has gained significant prominence as a powerful imaging technique in the field of life sciences. This comprehensive review provides an in-depth overview of recent advancements in ToF-SIMS instrument technology and its applications in metabolomics, lipidomics, and single-cell analysis. We highlight the use of ToF-SIMS imaging for studying lipid distribution, composition, and interactions in cells and tissues, and discuss its application in metabolomics, including the analysis of metabolic pathways. Furthermore, we review recent progress in single-cell analysis using ToF-SIMS, focusing on sample preparation techniques, in situ investigation for subcellular distribution of drugs, and interactions between drug molecules and biological targets. The high spatial resolution and potential for multimodal analysis of ToF-SIMS make it a promising tool for unraveling the complex molecular landscape of biological systems. We also discuss future prospects and potential advancements of ToF-SIMS in the research of life sciences, with the expectation of a significant impact in the field.
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Affiliation(s)
- Feifei Jia
- National Institutes for Food and Drug Control, Beijing, China
| | - Xia Zhao
- National Institutes for Food and Drug Control, Beijing, China
| | - Yao Zhao
- Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, CAS Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, China
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6
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Hu R, Li Y, Yang Y, Liu M. Mass spectrometry-based strategies for single-cell metabolomics. MASS SPECTROMETRY REVIEWS 2023; 42:67-94. [PMID: 34028064 DOI: 10.1002/mas.21704] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 05/05/2021] [Accepted: 05/11/2021] [Indexed: 06/12/2023]
Abstract
Single cell analysis has drawn increasing interest from the research community due to its capability to interrogate cellular heterogeneity, allowing refined tissue classification and facilitating novel biomarker discovery. With the advancement of relevant instruments and techniques, it is now possible to perform multiple omics including genomics, transcriptomics, metabolomics or even proteomics at single cell level. In comparison with other omics studies, single-cell metabolomics (SCM) represents a significant challenge since it involves many types of dynamically changing compounds with a wide range of concentrations. In addition, metabolites cannot be amplified. Although difficult, considerable progress has been made over the past decade in mass spectrometry (MS)-based SCM in terms of processing technologies and biochemical applications. In this review, we will summarize recent progress in the development of promising MS platforms, sample preparation methods and SCM analysis of various cell types (including plant cell, cancer cell, neuron, embryo cell, and yeast cell). Current limitations and future research directions in the field of SCM will also be discussed.
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Affiliation(s)
- Rui Hu
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ying Li
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yunhuang Yang
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Maili Liu
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
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7
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Chen Y, Chen P, Zhang T, Cao Y, Hua L, Li H. Design method and construction of the Schwarzschild microscope with high numerical aperture for secondary ion mass spectrometry. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2023; 94:013701. [PMID: 36725557 DOI: 10.1063/5.0128170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 12/15/2022] [Indexed: 06/18/2023]
Abstract
The Schwarzschild microscope is suitable for sample navigation in secondary ion mass spectrometry (SIMS) because of its advantages of a simple structure, large working distance, and good coordination with the ion extraction system. The high numerical aperture (NA) of the microscope significantly reduces diffraction effects, but the resulting high-order geometric aberrations seriously affect the imaging quality. In this paper, a novel design method of the Schwarzschild microscope with a high NA (0.47) was proposed. The aberration distributions and compensation methods were investigated through tolerance analysis. The results showed that the tilt and decenter tolerances become the dominant factors limiting the spatial resolution, which could only be improved by ensuring the alignment accuracy of mirrors. Finally, the spatial resolution of the microscope in the home-built SIMS reached 2.19 µm.
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Affiliation(s)
- Yi Chen
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, People's Republic of China
| | - Ping Chen
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, People's Republic of China
| | - Tao Zhang
- College of Instrumentation and Electrical Engineering, Jilin University, 938 Ximinzhu Road, Changchun, Jilin 130061, People's Republic of China
| | - Yixue Cao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, People's Republic of China
| | - Lei Hua
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, People's Republic of China
| | - Haiyang Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, People's Republic of China
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8
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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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9
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Penen F, Raavé R, Kip A, Heskamp S, Malmberg P. Time of Flight Secondary Ion Mass Spectrometry imaging for precise localization of zirconium-labelled trastuzumab in xenograft cancer tumour tissues. Microchem J 2022. [DOI: 10.1016/j.microc.2022.107860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
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10
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Gawne P, Man F, Blower PJ, T. M. de Rosales R. Direct Cell Radiolabeling for in Vivo Cell Tracking with PET and SPECT Imaging. Chem Rev 2022; 122:10266-10318. [PMID: 35549242 PMCID: PMC9185691 DOI: 10.1021/acs.chemrev.1c00767] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Indexed: 02/07/2023]
Abstract
The arrival of cell-based therapies is a revolution in medicine. However, its safe clinical application in a rational manner depends on reliable, clinically applicable methods for determining the fate and trafficking of therapeutic cells in vivo using medical imaging techniques─known as in vivo cell tracking. Radionuclide imaging using single photon emission computed tomography (SPECT) or positron emission tomography (PET) has several advantages over other imaging modalities for cell tracking because of its high sensitivity (requiring low amounts of probe per cell for imaging) and whole-body quantitative imaging capability using clinically available scanners. For cell tracking with radionuclides, ex vivo direct cell radiolabeling, that is, radiolabeling cells before their administration, is the simplest and most robust method, allowing labeling of any cell type without the need for genetic modification. This Review covers the development and application of direct cell radiolabeling probes utilizing a variety of chemical approaches: organic and inorganic/coordination (radio)chemistry, nanomaterials, and biochemistry. We describe the key early developments and the most recent advances in the field, identifying advantages and disadvantages of the different approaches and informing future development and choice of methods for clinical and preclinical application.
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Affiliation(s)
- Peter
J. Gawne
- School
of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, London, SE1 7EH, U.K.
| | - Francis Man
- School
of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, London, SE1 7EH, U.K.
- Institute
of Pharmaceutical Science, School of Cancer
and Pharmaceutical Sciences, King’s College London, London, SE1 9NH, U.K.
| | - Philip J. Blower
- School
of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, London, SE1 7EH, U.K.
| | - Rafael T. M. de Rosales
- School
of Biomedical Engineering & Imaging Sciences, King’s College London, St Thomas’ Hospital, London, SE1 7EH, U.K.
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11
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12
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Wang Y, Xia B, Deng S, Ye Y, Zhou Y. Performing 2D-1D-2D Mass Spectrometry Imaging Using Strings. Anal Chem 2022; 94:1661-1668. [PMID: 35029371 DOI: 10.1021/acs.analchem.1c04181] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The mass spectrometry imaging (MSI) technique is widely used in several fields due to its ability to provide spatial information of samples. However, for existing MSI methods, the sample is typically placed on a two-dimensional (2D) platform and is scanned back and forth. As a result, the platform size limits the imaging size. This paper proposes a new MSI method that involves the initial imprinting of chemicals on a two-dimensional string plane area. The string plane was then unraveled to a one-dimensional (1D) string, and the chemicals imprinted on it were ionized using a lab-made ion source. Finally, a 2D MSI image was reconstructed through data processing (2D-1D-2D mass imaging). Compared with traditional MSI methods, the imaging size is no longer limited by the platform size, making it possible to perform the MSI of large samples. As proof of concept, this method was used to image an intact seedling of Broussonetia papyrifera. As a result, clear and overall MS images were obtained, demonstrating the ability of this method to analyze large samples.
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Affiliation(s)
- Yu Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Bing Xia
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China
| | - Shunyan Deng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ye Ye
- Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
| | - Yan Zhou
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China
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13
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Analysis of the intracellular localization of amiodarone using live single-cell mass spectrometry. J Pharm Biomed Anal 2021; 205:114318. [PMID: 34418674 DOI: 10.1016/j.jpba.2021.114318] [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: 06/15/2021] [Revised: 08/06/2021] [Accepted: 08/07/2021] [Indexed: 01/08/2023]
Abstract
Amiodarone is a well-known antiarrhythmic drug with side effects including phospholipidosis. However, it is not clear how amiodarone and its metabolites are localized in the cell. In the present study, the localization of amiodarone in the cytosol, vacuoles, and lipid droplets of a single HepG2 human hepatocellular carcinoma cell was determined directly using live single-cell mass spectrometry. The cytosol, vacuoles, and lipid droplets of a single HepG2 cell treated with amiodarone were separately captured using a nano-spray tip under a fluorescence microscope after visualizing the lipid droplets using a fluorescent probe. This assay showed a linearity in the measurement of amiodarone levels with R2 values of 0.9996 and 0.9998 in the cell lysates and serum, respectively. The peak intensities of amiodarone and its metabolites in lipid droplets and vacuoles were significantly higher than those in the cytosol, while those in lipid droplets were higher than those in vacuoles. Amiodarone metabolites were detected in both lipid droplets and the cytosol. Live single-cell mass spectrometry combined with fluorescence imaging demonstrated clear localization of amiodarone and its metabolites in lipid droplets separately from the vacuole. This assay system combined with fluorescence imaging could be useful for investigating the intracellular localization of various drugs and their metabolites.
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Current and emerging mass spectrometry methods for the preclinical development of metal-based drugs: a critical appraisal. Anal Bioanal Chem 2021; 414:95-102. [PMID: 34642780 DOI: 10.1007/s00216-021-03718-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 09/23/2021] [Accepted: 10/04/2021] [Indexed: 10/20/2022]
Abstract
This Trends article highlights the multiple ways in which the state-of-the-art molecular mass spectrometry can support the preclinical development of novel metal-based anticancer drugs. Examples from the recent literature-beyond routine characterization applications-are presented to illustrate what analytical and experimental design challenges are to be addressed to facilitate the translation of promising drug candidates to clinical practice.
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Cahill JF, Kertesz V. Quantitation of amiodarone and N-desethylamiodarone in single HepG2 cells by single-cell printing-liquid vortex capture-mass spectrometry. Anal Bioanal Chem 2021; 413:6917-6927. [PMID: 34595558 DOI: 10.1007/s00216-021-03652-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 09/01/2021] [Accepted: 09/03/2021] [Indexed: 10/20/2022]
Abstract
Quantitative measure of a drug and its associated metabolite(s) with single-cell resolution is often limited by sampling throughput or other compromises that limit broad use. Here, we demonstrate the use of single-cell printing-liquid vortex capture-mass spectrometry (SCP-LVC-MS) to quantitatively measure the intracellular concentrations of amiodarone (AMIO) and its metabolite, N-desethylamiodarone (NDEA), from thousands of single cells across several AMIO incubation concentrations ranging from 0 to 10 μM. Concentrations obtained by SCP-LVC-MS were validated through comparison with average assays and traditional measurement of cells in bulk. Average of SCP-LVC-MS measurements and aggregate vial collection assay the concentrations differed by < 5%. Both AMIO and NDEA had clear log-normal distributions with similar standard deviation of concentrations in the cell population. The mean of both AMIO and NDEA intracellular concentrations were positively correlated with AMIO incubation concentration, increasing from 0.026 to 0.520 and 0.0055 to 0.048 mM for AMIO and NDEA, respectively. The standard deviation of AMIO and NDEA log-normal distribution fits were relatively similar in value across incubation concentrations, 0.15-0.19 log10 (mM), and exhibited a linear trend with respect to each other. The single cell-resolved conversion ratio of AMIO to NDEA increased with decreasing incubation concentration, 7 ± 2%, 18 ± 3%, and 20 ± 7% for 10.0, 1.0, and 0.1 μM AMIO incubation concentrations, respectively. Association with simultaneously measured lipids had several ions with statistically significant difference in intensity but no clear correlations with AMIO intracellular content was observed.
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Affiliation(s)
- John F Cahill
- Bioanalytical Mass Spectrometry Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831-6131, USA.
| | - Vilmos Kertesz
- Bioanalytical Mass Spectrometry Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831-6131, USA
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Yin L, Zhang Z, Liu Y, Gao Y, Gu J. Recent advances in single-cell analysis by mass spectrometry. Analyst 2019; 144:824-845. [PMID: 30334031 DOI: 10.1039/c8an01190g] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Cells are the most basic structural units that play vital roles in the functioning of living organisms. Analysis of the chemical composition and content of a single cell plays a vital role in ensuring precise investigations of cellular metabolism, and is a crucial aspect of lipidomic and proteomic studies. In addition, structural knowledge provides a better understanding of cell behavior as well as the cellular and subcellular mechanisms. However, single-cell analysis can be very challenging due to the very small size of each cell as well as the large variety and extremely low concentrations of substances found in individual cells. On account of its high sensitivity and selectivity, mass spectrometry holds great promise as an effective technique for single-cell analysis. Numerous mass spectrometric techniques have been developed to elucidate the molecular profiles at the cellular level, including electrospray ionization mass spectrometry (ESI-MS), secondary ion mass spectrometry (SIMS), laser-based mass spectrometry and inductively coupled plasma mass spectrometry (ICP-MS). In this review, the recent advances in single-cell analysis by mass spectrometry are summarized. The strategies of different ionization modes to achieve single-cell analysis are classified and discussed in detail.
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Affiliation(s)
- Lei Yin
- Research Institute of Translational Medicine, The First Hospital of Jilin University, Jilin University, Dongminzhu Street, Changchun 130061, PR China.
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Cahill JF, Riba J, Kertesz V. Rapid, Untargeted Chemical Profiling of Single Cells in Their Native Environment. Anal Chem 2019; 91:6118-6126. [DOI: 10.1021/acs.analchem.9b00680] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- John F. Cahill
- Mass Spectrometry and Laser Spectroscopy Group, Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6131, United States
| | - Julian Riba
- Laboratory for MEMS Applications, IMTEK - Department of Microsystems Engineering, University of Freiburg, Georges-Köhler-Allee 103, 79110 Freiburg, Germany
- Cytena GmbH, Neuer Messplatz 3, 79108 Freiburg, Germany
| | - Vilmos Kertesz
- Mass Spectrometry and Laser Spectroscopy Group, Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6131, United States
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Duncan KD, Fyrestam J, Lanekoff I. Advances in mass spectrometry based single-cell metabolomics. Analyst 2019; 144:782-793. [DOI: 10.1039/c8an01581c] [Citation(s) in RCA: 131] [Impact Index Per Article: 26.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Single cell metabolomics using mass spectrometry can contribute to understanding biological activities in health and disease.
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SHAO CF, ZHAO Y, WU K, JIA FF, LUO Q, LIU Z, WANG FY. Correlated Secondary Ion Mass Spectrometry-Laser Scanning Confocal Microscopy Imaging for Single Cell-Principles and Applications. CHINESE JOURNAL OF ANALYTICAL CHEMISTRY 2018. [DOI: 10.1016/s1872-2040(18)61095-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Rae Buchberger A, DeLaney K, Johnson J, Li L. Mass Spectrometry Imaging: A Review of Emerging Advancements and Future Insights. Anal Chem 2018; 90:240-265. [PMID: 29155564 PMCID: PMC5959842 DOI: 10.1021/acs.analchem.7b04733] [Citation(s) in RCA: 569] [Impact Index Per Article: 94.8] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Amanda Rae Buchberger
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Kellen DeLaney
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Jillian Johnson
- School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, Wisconsin 53705, United States
| | - Lingjun Li
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
- School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, Wisconsin 53705, United States
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