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Zou Z, Peng Z, Bhusal D, Wije Munige S, Yang Z. MassLite: An integrated python platform for single cell mass spectrometry metabolomics data pretreatment with graphical user interface and advanced peak alignment method. Anal Chim Acta 2024; 1325:343124. [PMID: 39244309 DOI: 10.1016/j.aca.2024.343124] [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: 04/14/2024] [Revised: 08/07/2024] [Accepted: 08/18/2024] [Indexed: 09/09/2024]
Abstract
Mass spectrometry (MS) has been one of the most widely used tools for bioanalytical analysis due to its high sensitivity, capability of quantitative analysis, and compatibility with biomolecules. Among various MS techniques, single cell mass spectrometry (SCMS) is an advanced approach to molecular analysis of cellular contents in individual cells. In tandem with the creation of novel experimental techniques, the development of new SCMS data analysis tools is equally important. As most published software packages are not specifically designed for pretreatment of SCMS data, including peak alignment and background removal, their applicability on processing SCMS data is generally limited. Hereby we introduce a Python platform, MassLite, specifically designed for rapid SCMS metabolomics data pretreatment. This platform is made user-friendly with graphical user interface (GUI) and exports data in the forms of each individual cell for further analysis. A core function of this tool is to use a novel peak alignment method that avoids the intrinsic drawbacks of traditional binning method, allowing for more effective handling of MS data obtained from high resolution mass spectrometers. Other functions, such as void scan filtering, dynamic grouping, and advanced background removal, are also implemented in this tool to improve pretreatment efficiency.
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Affiliation(s)
- Zhu Zou
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA
| | - Zongkai Peng
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA
| | - Deepti Bhusal
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA
| | - Shakya Wije Munige
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA.
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Pandian K, de Matos LDDAHEA, Hetzel LA, Zwier R, Veldhuizen PV, Schubert C, Karuppusamy J, Harms AC, Ali A, Hankemeier T. Enabling high-sensitivity live single-cell mass spectrometry using an integrated electrical lysis and nano electrospray ionization interface. Anal Chim Acta 2024; 1324:343068. [PMID: 39218570 DOI: 10.1016/j.aca.2024.343068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 08/03/2024] [Accepted: 08/05/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Live single-cell metabolomic studies encounter inherent difficulties attributed to the limited sample volume, minimal compound quantity, and insufficient sensitivity in the Mass Spectrometry (MS) method used to obtain single-cell data. However, understanding cellular heterogeneity, functional diversity, and metabolic processes within individual cells is essential. Exploring how individual cells respond to stimuli, including drugs, environmental changes, or signaling molecules, offers insights into biology, oncology, and drug discovery. Efficient release of cell contents (lysis) is vital for accurate metabolite detection at the single-cell level. Despite this, traditional approaches in live single cell metabolomics methods do not emphasize efficient lysis to prevent sample dilution. Instead, current live single cell metabolomics methods use direct infusion to introduce the cell into the mass spectrometry without prior chromatographic separation or a lysis step, which adversely affects sensitivity and metabolic coverage. RESULTS To address this, we developed an integrated single-cell electrical lysis and nano spray (SCEL-nS) platform coupled to an Orbitrap MS capable of efficiently lysing a single cell after being sampled with specially manufactured micropipettes. Lysis efficiency was validated by comparing live cell stain fluorescent intensities of intact and electrically lysed cells through microscopy imaging. The SCEL-nS platform successfully induced the breakdown of a single cell, significantly reducing the live cell stain's fluorescent intensity indicating cell membrane breakdown. Additionally, SCEL-nS was validated by measuring single cells spiked with the anti-cancer drug tamoxifen by MS. SCEL-nS use resulted in statistically significant increase in the peak measured by the method compared to the traditional non-lysis method. SIGNIFICANCE Overall, our results demonstrate that the newly incorporated SCEL-nS platform achieved higher sensitivities compared to traditional live single cell analysis methods.
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Affiliation(s)
- Kanchana Pandian
- Metabolomics and Analytics Center, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | | | - Laura A Hetzel
- Metabolomics and Analytics Center, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | - Raphaël Zwier
- Fine Mechanical Department, Leiden Institute of Physics (LION), Leiden University, Leiden, the Netherlands
| | - Peter van Veldhuizen
- Electronics Department, Leiden Institute of Physics (LION), Leiden University, Leiden, the Netherlands
| | - Charelle Schubert
- Metabolomics and Analytics Center, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | - Jayaprakash Karuppusamy
- Department of Mechanical Engineering, Birla Institute of Technology and Science, Pilani, Hyderabad, India
| | - Amy C Harms
- Metabolomics and Analytics Center, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | - Ahmed Ali
- Metabolomics and Analytics Center, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands.
| | - Thomas Hankemeier
- Metabolomics and Analytics Center, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
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Xiao Y, Li Y, Zhao H. Spatiotemporal metabolomic approaches to the cancer-immunity panorama: a methodological perspective. Mol Cancer 2024; 23:202. [PMID: 39294747 PMCID: PMC11409752 DOI: 10.1186/s12943-024-02113-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Accepted: 09/05/2024] [Indexed: 09/21/2024] Open
Abstract
Metabolic reprogramming drives the development of an immunosuppressive tumor microenvironment (TME) through various pathways, contributing to cancer progression and reducing the effectiveness of anticancer immunotherapy. However, our understanding of the metabolic landscape within the tumor-immune context has been limited by conventional metabolic measurements, which have not provided comprehensive insights into the spatiotemporal heterogeneity of metabolism within TME. The emergence of single-cell, spatial, and in vivo metabolomic technologies has now enabled detailed and unbiased analysis, revealing unprecedented spatiotemporal heterogeneity that is particularly valuable in the field of cancer immunology. This review summarizes the methodologies of metabolomics and metabolic regulomics that can be applied to the study of cancer-immunity across single-cell, spatial, and in vivo dimensions, and systematically assesses their benefits and limitations.
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Affiliation(s)
- Yang Xiao
- Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, 400044, China
| | - Yongsheng Li
- Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, 400044, China.
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing, 400030, China.
| | - Huakan Zhao
- Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, 400044, China.
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing, 400030, China.
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4
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Ren A, Chen F, Ren C, Yang M, Wang C, Feng X, Zhang F. Rapid Screening of Biomarkers in KYSE-150 Cells Exposed to Polycyclic Aromatic Hydrocarbons via Inkjet Printing Single-Cell Mass Spectrometry. Anal Chem 2024; 96:12817-12826. [PMID: 39052489 DOI: 10.1021/acs.analchem.4c02332] [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: 07/27/2024]
Abstract
Single-cell analysis by mass spectrometry (MS) is emerging as a powerful tool that not only contributes to cellular heterogeneity but also offers an unprecedented opportunity to predict pathology onset and facilitates novel biomarker discovery. However, the development of single-cell MS analysis techniques with a focus on sample extraction, separation, and ionization methods for volume-limited samples and complexity of cellular samples are still a big challenge. In this study, we present a high-throughput approach to inkjet drop on demand printing single-cell MS for rapid screening of biomarkers of polycyclic aromatic hydrocarbon (PAH) exposure at the KYSE-150 cell, aiming to elucidate the pathogenesis of PAH-induced esophageal cancer. With an analytical bulk KYSE-150 cell throughput of up to 51 cells per minute, the method provides a new opportunity for simultaneous single-cell analysis of multiple biomarkers. We screened 930 characteristic ions from 3,683 detected peak signals and identified 91 distinctive molecules that exhibited significant differences under various concentrations of PAH exposure. These molecules have potential as clinical diagnostic biomarkers. Additionally, the current study identifies specific biomarkers that behave completely opposite in single-cell and multicell lipidomics as the concentration of PAH changes. These biomarkers potentially subdivide KYSE-150 cells into PAH-sensitive and PAH-insensitive types, providing a basis for revealing PAH toxicity and disease pathogenesis from the heterogeneity of cellular metabolism.
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Affiliation(s)
- Ai Ren
- Institute of Food Safety, Chinese Academy of Inspection and Quarantine, Beijing 100176, China
- Key Laboratory of Food Quality and Safety for State Market Regulation, School of Pharmacy, China Medical University, Shenyang 110122, China
| | - Fengming Chen
- Institute of Food Safety, Chinese Academy of Inspection and Quarantine, Beijing 100176, China
- Key Laboratory of Food Quality and Safety for State Market Regulation, School of Pharmacy, China Medical University, Shenyang 110122, China
| | - Chenjie Ren
- Institute of Food Safety, Chinese Academy of Inspection and Quarantine, Beijing 100176, China
- Key Laboratory of Food Quality and Safety for State Market Regulation, School of Pharmacy, China Medical University, Shenyang 110122, China
| | - Minli Yang
- Institute of Food Safety, Chinese Academy of Inspection and Quarantine, Beijing 100176, China
- Key Laboratory of Food Quality and Safety for State Market Regulation, School of Pharmacy, China Medical University, Shenyang 110122, China
| | - Chang Wang
- Institute of Food Safety, Chinese Academy of Inspection and Quarantine, Beijing 100176, China
- Key Laboratory of Food Quality and Safety for State Market Regulation, School of Pharmacy, China Medical University, Shenyang 110122, China
| | - Xuesong Feng
- School of Pharmacy, China Medical University, Shenyang 110122, China
| | - Feng Zhang
- Institute of Food Safety, Chinese Academy of Inspection and Quarantine, Beijing 100176, China
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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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Taunk K, Jajula S, Bhavsar PP, Choudhari M, Bhanuse S, Tamhankar A, Naiya T, Kalita B, Rapole S. The prowess of metabolomics in cancer research: current trends, challenges and future perspectives. Mol Cell Biochem 2024:10.1007/s11010-024-05041-w. [PMID: 38814423 DOI: 10.1007/s11010-024-05041-w] [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: 12/21/2023] [Accepted: 05/18/2024] [Indexed: 05/31/2024]
Abstract
Cancer due to its heterogeneous nature and large prevalence has tremendous socioeconomic impacts on populations across the world. Therefore, it is crucial to discover effective panels of biomarkers for diagnosing cancer at an early stage. Cancer leads to alterations in cell growth and differentiation at the molecular level, some of which are very unique. Therefore, comprehending these alterations can aid in a better understanding of the disease pathology and identification of the biomolecules that can serve as effective biomarkers for cancer diagnosis. Metabolites, among other biomolecules of interest, play a key role in the pathophysiology of cancer whose levels are significantly altered while 'reprogramming the energy metabolism', a cellular condition favored in cancer cells which is one of the hallmarks of cancer. Metabolomics, an emerging omics technology has tremendous potential to contribute towards the goal of investigating cancer metabolites or the metabolic alterations during the development of cancer. Diverse metabolites can be screened in a variety of biofluids, and tumor tissues sampled from cancer patients against healthy controls to capture the altered metabolism. In this review, we provide an overview of different metabolomics approaches employed in cancer research and the potential of metabolites as biomarkers for cancer diagnosis. In addition, we discuss the challenges associated with metabolomics-driven cancer research and gaze upon the prospects of this emerging field.
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Affiliation(s)
- Khushman Taunk
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
- Department of Biotechnology, Maulana Abul Kalam Azad University of Technology, West Bengal, NH12 Simhat, Haringhata, Nadia, West Bengal, 741249, India
| | - Saikiran Jajula
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Praneeta Pradip Bhavsar
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Mahima Choudhari
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Sadanand Bhanuse
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Anup Tamhankar
- Department of Surgical Oncology, Deenanath Mangeshkar Hospital and Research Centre, Erandawne, Pune, Maharashtra, 411004, India
| | - Tufan Naiya
- Department of Biotechnology, Maulana Abul Kalam Azad University of Technology, West Bengal, NH12 Simhat, Haringhata, Nadia, West Bengal, 741249, India
| | - Bhargab Kalita
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India.
- Amrita School of Nanosciences and Molecular Medicine, Amrita Institute of Medical Sciences and Research Centre, Amrita Vishwa Vidyapeetham, Ponekkara, Kochi, Kerala, 682041, India.
| | - Srikanth Rapole
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India.
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Cheng S, Cao C, Qian Y, Yao H, Gong X, Dai X, Ouyang Z, Ma X. High-throughput single-cell mass spectrometry enables metabolic network analysis by resolving phospholipid C[double bond, length as m-dash]C isomers. Chem Sci 2024; 15:6314-6320. [PMID: 38699276 PMCID: PMC11062128 DOI: 10.1039/d3sc06573a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/02/2024] [Indexed: 05/05/2024] Open
Abstract
Single-cell mass spectrometry (MS) is an essential technology for sensitive and multiplexed analysis of metabolites and lipids for cell phenotyping and pathway studies. However, the structural elucidation of lipids from single cells remains a challenge, especially in the high-throughput scenario. Technically, there is a contradiction between the inadequate sample amount (i.e. a single cell, 0.5-20 pL) for replicate or multiple analysis, on the one hand, and the high metabolite coverage and multidimensional structure analysis that needs to be performed for each single cell, on the other hand. Here, we have developed a high-throughput single-cell MS platform that can perform both lipid profiling and lipid carbon-carbon double bond (C[double bond, length as m-dash]C) location isomer resolution analysis, aided by C[double bond, length as m-dash]C activation in unsaturated lipids by the Paternò-Büchi (PB) reaction and tandem MS, termed single-cell structural lipidomics analysis. The method can achieve a single-cell analysis throughput of 51 cells per minute. A total of 145 lipids were structurally characterized at the subclass level, of which the relative abundance of 17 isomeric lipids differing in the location of C[double bond, length as m-dash]C from 5 lipid precursors was determined. While cell-to-cell variations in MS1-based lipid profiling can be large, an advantage of quantifying lipid C[double bond, length as m-dash]C location isomers is the significantly improved quantitation accuracy. For example, the relative standard deviations (RSDs) of the relative amounts of PC 34:1 C[double bond, length as m-dash]C position isomers in MDA-MB-468 cells are half smaller than those measured for PC 34:1 as a whole by MS1 abundance profiling. Taken together, the developed method can be effectively used for in-depth structural lipid metabolism network analysis by high-throughput analysis of 142 MDA-MB-468 human breast cancer cells.
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Affiliation(s)
- Simin Cheng
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology Bejing 100029 China
| | - Chenxi Cao
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University Beijing 100084 China
| | - Yao Qian
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University Beijing 100084 China
| | - Huan Yao
- Division of Chemical Metrology and Analytical Science, National Institute of Metrology Beijing 100029 China
| | - Xiaoyun Gong
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology Bejing 100029 China
| | - Xinhua Dai
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology Bejing 100029 China
| | - Zheng Ouyang
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University Beijing 100084 China
| | - Xiaoxiao Ma
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University Beijing 100084 China
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8
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Zhou Y, Wu Q, Zhao Z, Wang Y, Lu H. Photocatalytic degradation-based ambient mass spectrometry imaging for enhancing detection coverage of poorly-ionizable lipidomes. Talanta 2024; 270:125564. [PMID: 38159350 DOI: 10.1016/j.talanta.2023.125564] [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: 12/15/2023] [Accepted: 12/16/2023] [Indexed: 01/03/2024]
Abstract
Localization of lipidomes and tracking their spatial changes in tissues by mass spectrometry imaging (MSI) plays an important role in unveiling the mechanisms of living processes, diseases and therapeutic treatments. However, it is always challenging to achieve direct MSI of poorly-ionizable lipids, such as glycolipids and glycerolipids, due to the strong ion suppression and isobaric peaks interference from high-abundance phosphatidylcholines (PCs) in tissues. Here we developed a photocatalytic degradation-based ambient liquid extraction MSI method to largely enhance the detection coverage of poorly-ionizable lipids by rapid online removal of PCs in MSI. Phospholipids were found to be selectively photodegraded on TiO2 surface in acidic conditions in the presence of water under UV irradiation, while other poorly-ionizable lipids remained. Sulfate ion could largely improve the degradation efficiencies. Anatase nanoparticles-embedded TiO2 monolith was in-situ synthesized in the capillary of ambient liquid extraction system, and rapid online photodegradation of PCs was achieved during MSI with efficiency >80 %, largely reducing ion suppression. The pathway analysis showed that PC was oxidatively degraded starting from hydroxylation of C=C bonds. With intense UV irradiation, PCs were completely degraded into small molecules<200 Da without interference on the detection of endogenous lipids. With the new MSI method, detection coverage to cerebrosides, ceramides and diglycerides was enhanced by 2-9 times comparing with traditional MSI. Clearer localizations were observed for poorly-ionizable lipids via the new method than traditional method. Thus, this work provided a complementary MSI method for traditional MSI to address the issues on direct imaging of poorly ionizable lipids in ambient conditions.
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Affiliation(s)
- Yongchang Zhou
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha, 410083, PR China
| | - Qian Wu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha, 410083, PR China.
| | - Zhihao Zhao
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha, 410083, PR China
| | - Yang Wang
- Laboratory of Ethnopharmacology, Institute of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Hunan, Changsha, 410008, PR China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha, 410083, PR China
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9
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Xu T, Li H, Dou P, Luo Y, Pu S, Mu H, Zhang Z, Feng D, Hu X, Wang T, Tan G, Chen C, Li H, Shi X, Hu C, Xu G. Concentric Hybrid Nanoelectrospray Ionization-Atmospheric Pressure Chemical Ionization Source for High-Coverage Mass Spectrometry Analysis of Single-Cell Metabolomics. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2306659. [PMID: 38359005 DOI: 10.1002/advs.202306659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 02/04/2024] [Indexed: 02/17/2024]
Abstract
High-coverage mass spectrometry analysis of single-cell metabolomics remains challenging due to the extremely low abundance and wide polarity of metabolites and ultra-small volume in single cells. Herein, a novel concentric hybrid ionization source, nanoelectrospray ionization-atmospheric pressure chemical ionization (nanoESI-APCI), is ingeniously designed to detect polar and nonpolar metabolites simultaneously in single cells. The source is constructed by inserting a pulled glass capillary coaxially into a glass tube that acts as a dielectric barrier layer. Benefitting from the integrated advantages of nanoESI and APCI, its limit of detection is improved by one order of magnitude to 10 pg mL-1. After the operational parameter optimization, 254 metabolites detected in nanoESI-APCI are tentatively identified from a single cell, and 82 more than those in nanoESI. The developed nanoESI-APCI is successively applied to study the metabolic heterogeneity of human hepatocellular carcinoma tissue microenvironment united with laser capture microdissection (LCM), the discrimination of cancer cell types and subtypes, the metabolic perturbations to glucose starvation in MCF7 cells and the metabolic regulation of cancer stem cells. These results demonstrated that the nanoESI-APCI not only opens a new avenue for high-coverage and high-sensitivity metabolomics analysis of single cell, but also facilitates spatially resolved metabolomics study coupled with LCM.
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Affiliation(s)
- Tianrun Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
| | - Hang Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
| | - Peng Dou
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
| | - Yuanyuan Luo
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
| | - Siming Pu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
| | - Hua Mu
- The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116023, P. R. China
| | - Zhihao Zhang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Science, Dalian Key Laboratory for Online Analytical Instrumentation, Dalian, Liaoning, 116023, P. R. China
| | - Disheng Feng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
| | - Xuesen Hu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
| | - Ting Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
| | - Guang Tan
- The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, 116023, P. R. China
| | - Chuang Chen
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Science, Dalian Key Laboratory for Online Analytical Instrumentation, Dalian, Liaoning, 116023, P. R. China
| | - Haiyang Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Science, Dalian Key Laboratory for Online Analytical Instrumentation, Dalian, Liaoning, 116023, P. R. China
| | - Xianzhe Shi
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
| | - Chunxiu Hu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences (CAS), University of Chinese Academy of Sciences, Liaoning Province Key Laboratory of Metabolomics, Dalian, Liaoning, 116023, P. R. China
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10
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Cheng KW, Su PR, Feller KJA, Chien MP, Hsu CC. Investigating the Metabolic Heterogeneity of Cancer Cells Using Functional Single-Cell Selection and nLC Combined with Multinozzle Emitter Mass Spectrometry. Anal Chem 2024; 96:624-629. [PMID: 38157203 DOI: 10.1021/acs.analchem.3c03688] [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: 01/03/2024]
Abstract
Tumor metastasis and cancer recurrence are often a result of cell heterogeneity, where specific subpopulations of tumor cells may be resistant to radio- or chemotherapy. To investigate this physiological and phenotypic diversity, single-cell metabolomics provides a powerful approach at the chemical level, where distinct lipid profiles can be found in different tumor cells. Here, we established a highly sensitive platform using nanoflow liquid chromatography (nLC) combined with multinozzle emitter electrospray ionization mass spectrometry for more in-depth metabolomics profiling. Our platform identified 15 and 17 lipids from individual osteosarcoma (U2OS) and glioblastoma (GBM) cells when analyzing single-cell samples. Additionally, we used the functional single-cell selection (fSCS) pipeline to analyze the subpopulations of cells with a DNA damage response (DDR) in U2OS cells and fast migration in GBM cells. Specifically, we observed a down-regulation of polyunsaturated fatty acids (PUFAs) in U2OS cells undergoing DDR, such as fatty acids FA 20:3; O2 and FA 17:4; O3. Furthermore, ceramides (Cer 38:0; O3) and triglycerides (TG 36:0) were found to be down-regulated in fast-migrating GBM cells compared to the slow-migrating subpopulation. These findings suggest the potential roles of these metabolites and/or lipids in the cellular behavior of the subpopulations.
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Affiliation(s)
- Kai-Wen Cheng
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Pin-Rui Su
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
- Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
- Oncode Institute, 3521 AL Utrecht, The Netherlands
| | - Kate Jo-Ann Feller
- Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
- Oncode Institute, 3521 AL Utrecht, The Netherlands
| | - Miao-Ping Chien
- Department of Molecular Genetics, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
- Oncode Institute, 3521 AL Utrecht, The Netherlands
| | - Cheng-Chih Hsu
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
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11
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Zhang D, Qiao L. Microfluidics Coupled Mass Spectrometry for Single Cell Multi-Omics. SMALL METHODS 2024; 8:e2301179. [PMID: 37840412 DOI: 10.1002/smtd.202301179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/02/2023] [Indexed: 10/17/2023]
Abstract
Population-level analysis masks significant heterogeneity between individual cells, making it difficult to accurately reflect the true intricacies of life activities. Microfluidics is a technique that can manipulate individual cells effectively and is commonly coupled with a variety of analytical methods for single-cell analysis. Single-cell omics provides abundant molecular information at the single-cell level, fundamentally revealing differences in cell types and biological states among cell individuals, leading to a deeper understanding of cellular phenotypes and life activities. Herein, this work summarizes the microfluidic chips designed for single-cell isolation, manipulation, trapping, screening, and sorting, including droplet microfluidic chips, microwell arrays, hydrodynamic microfluidic chips, and microchips with microvalves. This work further reviews the studies on single-cell proteomics, metabolomics, lipidomics, and multi-omics based on microfluidics and mass spectrometry. Finally, the challenges and future application of single-cell multi-omics are discussed.
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Affiliation(s)
- Dongxue Zhang
- Department of Chemistry, Institutes of Biomedical Sciences, and Minhang Hospital, Fudan University, Shanghai, 20000, China
| | - Liang Qiao
- Department of Chemistry, Institutes of Biomedical Sciences, and Minhang Hospital, Fudan University, Shanghai, 20000, China
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12
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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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13
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Wevers D, Ramautar R, Clark C, Hankemeier T, Ali A. Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics. Electrophoresis 2023; 44:2000-2024. [PMID: 37667867 DOI: 10.1002/elps.202300105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 08/08/2023] [Accepted: 08/19/2023] [Indexed: 09/06/2023]
Abstract
Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.
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Affiliation(s)
- Dirk Wevers
- Wageningen University and Research, Wageningen, The Netherlands
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Rawi Ramautar
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Charlie Clark
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Thomas Hankemeier
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Ahmed Ali
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
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14
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Zhao Z, Long Z, Wang H, Wu Q, Wang Y, Lu H. Pulled Flowprobe for Ambient Liquid Extraction-Based High Spatial Resolution Mass Spectrometry Imaging with Enhanced Sensitivity and Stability. Anal Chem 2023; 95:16927-16935. [PMID: 37939311 DOI: 10.1021/acs.analchem.3c03046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Ambient liquid extraction techniques enable direct mass spectrometry imaging (MSI) under ambient conditions with minimal sample preparation. However, currently an integrated probe for ambient liquid extraction-based MSI with high spatial resolution, high sensitivity, and stability is still lacking. In this work, we developed a new integrated probe made of pulled coaxial capillaries, named pulled flowprobe, and compared it with the previously reported single-probe. Mass transfer kinetics in probes was first investigated. The extraction kinetic curves during probe sampling indicate a narrower and higher peak shape for the pulled flowprobe than single-probe. Computational fluid dynamics analysis reveals that in the pulled flowprobe flow velocities are lower in liquid microjunction and higher in the transferring channels, resulting in higher extraction efficiencies and reduced band diffusion compared with single-probe and other probes with a similar flow route. Results of ambient liquid extraction-based MSI of lipids in rat cerebrum show that signals of low-abundance lipids were 2-5 times higher via a pulled flowprobe than via a single-probe, and 26 more lipid species were detected on brain tissue via a pulled flowprobe than via a single-probe. The stability of MSI with the pulled flowprobe was found to be higher than that with single-probe (averaged relative standard deviation = 18% vs 80%) by imaging a lab-made uniform ink coating. Moreover, in the pulled flowprobe, no retraction of the inner capillary from outer capillary is optimal for both sensitivity and stability. The spatial resolution of the pulled flowprobe (30-40 μm) was measured to be higher than that of a comparable size single-probe by calculation with the "80-20" rule. Finally, the new pulled flowprobe was applied to high-resolution MSI of lipids in the hippocampus, and localization of several lipids to the specific cell layers in the hippocampus region was observed. Thus, this work provides an alternative easily fabricated sampling probe with enhanced sensitivity, stability, and spatial resolution, promoting the use of ambient liquid extraction-based MSI in biological and clinical research.
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Affiliation(s)
- Zhihao Zhao
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P. R. China
| | - Zheng Long
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P. R. China
| | - Huabei Wang
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P. R. China
| | - Qian Wu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P. R. China
| | - Yang Wang
- Laboratory of Ethnopharmacology, Institute of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Hunan, Changsha 410008, P. R. China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P. R. China
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15
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Weigand MR, Moore AM, Hu H, Angel PM, Drake RR, Laskin J. Imaging of N-Linked Glycans in Biological Tissue Sections Using Nanospray Desorption Electrospray Ionization (nano-DESI) Mass Spectrometry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2481-2490. [PMID: 37779241 DOI: 10.1021/jasms.3c00209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
N-linked glycans are complex biomolecules vital to cellular functions that have been linked to a wide range of pathological conditions. Mass spectrometry imaging (MSI) has been used to study the localization of N-linked glycans in cells and tissues. However, their structural diversity presents a challenge for MSI techniques, which stimulates the development of new approaches. In this study, we demonstrate for the first time spatial mapping of N-linked glycans in biological tissues using nanospray desorption electrospray ionization mass spectrometry imaging (nano-DESI MSI). Nano-DESI MSI is an ambient ionization technique that has been previously used for imaging of metabolites, lipids, and proteins in biological tissue samples without special sample pretreatment. N-linked glycans are released from glycoproteins using an established enzymatic digestion with peptide N-glycosidase F, and their spatial localization is examined using nano-DESI MSI. We demonstrate imaging of N-linked glycans in formalin-fixed paraffin-embedded human hepatocellular carcinoma and human prostate tissues in both positive and negative ionization modes. We examine the localization of 38 N-linked glycans consisting of high mannose, hybrid fucosylated, and sialyated glycans. We demonstrate that negative mode nano-DESI MSI is well-suited for imaging of underivatized sialylated N-linked glycans. On-tissue MS/MS of different adducts of N-linked glycans proves advantageous for elucidation of the glycan sequence. This study demonstrates the applicability of liquid extraction techniques for spatial mapping of N-linked glycans in biological samples, providing an additional tool for glycobiology research.
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Affiliation(s)
- Miranda R Weigand
- Department of Chemistry, College of Science, Purdue University, West Lafayette, Indiana 47907, United States
| | - Alyssa M Moore
- Department of Chemistry, College of Science, Purdue University, West Lafayette, Indiana 47907, United States
| | - Hang Hu
- Department of Chemistry, College of Science, Purdue University, West Lafayette, Indiana 47907, United States
| | - Peggi M Angel
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, South Carolina 29425, United States
| | - Richard R Drake
- Department of Cell and Molecular Pharmacology and Experimental Therapeutics, Medical University of South Carolina, Charleston, South Carolina 29425, United States
| | - Julia Laskin
- Department of Chemistry, College of Science, Purdue University, West Lafayette, Indiana 47907, United States
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16
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Li X, Hu H, Laskin J. High-resolution integrated microfluidic probe for mass spectrometry imaging of biological tissues. Anal Chim Acta 2023; 1279:341830. [PMID: 37827646 PMCID: PMC10594281 DOI: 10.1016/j.aca.2023.341830] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 09/06/2023] [Accepted: 09/16/2023] [Indexed: 10/14/2023]
Abstract
Nanospray desorption electrospray ionization (nano-DESI) is an ambient ionization technique that enables molecular imaging of biological samples with high spatial resolution. We have recently developed an integrated microfluidic probe (iMFP) for nano-DESI mass spectrometry imaging (MSI) that significantly enhances the robustness of the technique. In this study, we designed a new probe that enables imaging of biological samples with high spatial resolution. The new probe design features smaller primary and spray channels and an entirely new configuration of the sampling port that enables robust imaging of tissues with a spatial resolution of 8-10 μm. We demonstrate the spatial resolution, sensitivity, durability, and throughput of the iMFP by imaging mouse uterine and brain tissue sections. The robustness of the high-resolution iMFP allowed us to perform first imaging experiments with both high spatial resolution and high throughput, which is particularly advantageous for high-resolution imaging of large tissue sections of interest to most MSI applications. Overall, the new probe design opens opportunities for mapping of biomolecules in biological samples with high throughput and cellular resolution, which is important for understanding biological systems.
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Affiliation(s)
- Xiangtang Li
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, United States
| | - Hang Hu
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, United States
| | - Julia Laskin
- Department of Chemistry, Purdue University, West Lafayette, IN, 47907, United States.
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17
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Saunders KD, von Gerichten J, Lewis HM, Gupta P, Spick M, Costa C, Velliou E, Bailey MJ. Single-Cell Lipidomics Using Analytical Flow LC-MS Characterizes the Response to Chemotherapy in Cultured Pancreatic Cancer Cells. Anal Chem 2023; 95:14727-14735. [PMID: 37725657 PMCID: PMC10551860 DOI: 10.1021/acs.analchem.3c02854] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 09/07/2023] [Indexed: 09/21/2023]
Abstract
In this work, we demonstrate the development and first application of nanocapillary sampling followed by analytical flow liquid chromatography-mass spectrometry for single-cell lipidomics. Around 260 lipids were tentatively identified in a single cell, demonstrating remarkable sensitivity. Human pancreatic ductal adenocarcinoma cells (PANC-1) treated with the chemotherapeutic drug gemcitabine can be distinguished from controls solely on the basis of their single-cell lipid profiles. Notably, the relative abundance of LPC(0:0/16:0) was significantly affected in gemcitabine-treated cells, in agreement with previous work in bulk. This work serves as a proof of concept that live cells can be sampled selectively and then characterized using automated and widely available analytical workflows, providing biologically relevant outputs.
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Affiliation(s)
| | | | - Holly-May Lewis
- Faculty
of Health & Medical Sciences, University
of Surrey, Guildford GU2 7XH, U.K.
| | - Priyanka Gupta
- Centre
for 3D Models of Health and Disease, University
College London—Division of Surgery and Interventional Science, London W1W 7TY, U.K.
| | - Matt Spick
- Faculty
of Health & Medical Sciences, University
of Surrey, Guildford GU2 7XH, U.K.
| | - Catia Costa
- Ion
Beam Centre, University of Surrey, Guildford GU2 7XH, U.K.
| | - Eirini Velliou
- Centre
for 3D Models of Health and Disease, University
College London—Division of Surgery and Interventional Science, London W1W 7TY, U.K.
| | - Melanie J. Bailey
- Department
of Chemistry, University of Surrey, Guildford GU2 7XH, U.K.
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18
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Pandian K, Matsui M, Hankemeier T, Ali A, Okubo-Kurihara E. Advances in single-cell metabolomics to unravel cellular heterogeneity in plant biology. PLANT PHYSIOLOGY 2023; 193:949-965. [PMID: 37338502 PMCID: PMC10517197 DOI: 10.1093/plphys/kiad357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/03/2023] [Accepted: 05/17/2023] [Indexed: 06/21/2023]
Abstract
Single-cell metabolomics is a powerful tool that can reveal cellular heterogeneity and can elucidate the mechanisms of biological phenomena in detail. It is a promising approach in studying plants, especially when cellular heterogeneity has an impact on different biological processes. In addition, metabolomics, which can be regarded as a detailed phenotypic analysis, is expected to answer previously unrequited questions which will lead to expansion of crop production, increased understanding of resistance to diseases, and in other applications as well. In this review, we will introduce the flow of sample acquisition and single-cell techniques to facilitate the adoption of single-cell metabolomics. Furthermore, the applications of single-cell metabolomics will be summarized and reviewed.
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Affiliation(s)
- Kanchana Pandian
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Einstein Road 55, 2333 CC Leiden, The Netherlands
| | - Minami Matsui
- RIKEN, Center for Sustainable Resource Science, Kanagawa 230-0045, Japan
| | - Thomas Hankemeier
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Einstein Road 55, 2333 CC Leiden, The Netherlands
| | - Ahmed Ali
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Einstein Road 55, 2333 CC Leiden, The Netherlands
| | - Emiko Okubo-Kurihara
- RIKEN, Center for Sustainable Resource Science, Kanagawa 230-0045, Japan
- College of Science, Rikkyo University, Tokyo 171-8501, Japan
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19
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Li W, Shao C, Li C, Zhou H, Yu L, Yang J, Wan H, He Y. Metabolomics: A useful tool for ischemic stroke research. J Pharm Anal 2023; 13:968-983. [PMID: 37842657 PMCID: PMC10568109 DOI: 10.1016/j.jpha.2023.05.015] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 05/14/2023] [Accepted: 05/29/2023] [Indexed: 10/17/2023] Open
Abstract
Ischemic stroke (IS) is a multifactorial and heterogeneous disease. Despite years of studies, effective strategies for the diagnosis, management and treatment of stroke are still lacking in clinical practice. Metabolomics is a growing field in systems biology. It is starting to show promise in the identification of biomarkers and in the use of pharmacometabolomics to help patients with certain disorders choose their course of treatment. The development of metabolomics has enabled further and more biological applications. Particularly, metabolomics is increasingly being used to diagnose diseases, discover new drug targets, elucidate mechanisms, and monitor therapeutic outcomes and its potential effect on precision medicine. In this review, we reviewed some recent advances in the study of metabolomics as well as how metabolomics might be used to identify novel biomarkers and understand the mechanisms of IS. Then, the use of metabolomics approaches to investigate the molecular processes and active ingredients of Chinese herbal formulations with anti-IS capabilities is summarized. We finally summarized recent developments in single cell metabolomics for exploring the metabolic profiles of single cells. Although the field is relatively young, the development of single cell metabolomics promises to provide a powerful tool for unraveling the pathogenesis of IS.
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Affiliation(s)
- Wentao Li
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Chongyu Shao
- School of Basic Medicine Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Chang Li
- School of Basic Medicine Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Huifen Zhou
- School of Basic Medicine Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Li Yu
- School of Basic Medicine Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Jiehong Yang
- School of Basic Medicine Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Haitong Wan
- School of Basic Medicine Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Yu He
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
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20
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Rerick MT, Chen J, Weber SG. Electroosmotic Perfusion, External Microdialysis: Simulation and Experiment. ACS Chem Neurosci 2023. [PMID: 37379416 PMCID: PMC10360060 DOI: 10.1021/acschemneuro.3c00057] [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: 06/30/2023] Open
Abstract
Information about the rates of hydrolysis of neuropeptides by extracellular peptidases can lead to a quantitative understanding of how the steady-state and transient concentrations of neuropeptides are controlled. We have created a small microfluidic device that electroosmotically infuses peptides into, through, and out of the tissue to a microdialysis probe outside the head. The device is created by two-photon polymerization (Nanoscribe). Inferring quantitative estimates of a rate process from the change in concentration of a substrate that has passed through tissue is challenging for two reasons. One is that diffusion is significant, so there is a distribution of peptide substrate residence times in the tissue. This affects the product yield. The other is that there are multiple paths taken by the substrate as it passes through tissue, so there is a distribution of residence times and thus reaction times. Simulation of the process is essential. The simulations presented here imply that a range of first order rate constants of more than 3 orders of magnitude is measurable and that 5-10 min is required to reach a steady state value of product concentration following initiation of substrate infusion. Experiments using a peptidase-resistant d-amino acid pentapeptide, yaGfl, agree with simulations.
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Affiliation(s)
- Michael T Rerick
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
| | - Jun Chen
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
| | - Stephen G Weber
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
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21
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Abstract
Lipids are essential cellular components forming membranes, serving as energy reserves, and acting as chemical messengers. Dysfunction in lipid metabolism and signaling is associated with a wide range of diseases including cancer and autoimmunity. Heterogeneity in cell behavior including lipid signaling is increasingly recognized as a driver of disease and drug resistance. This diversity in cellular responses as well as the roles of lipids in health and disease drive the need to quantify lipids within single cells. Single-cell lipid assays are challenging due to the small size of cells (∼1 pL) and the large numbers of lipid species present at concentrations spanning orders of magnitude. A growing number of methodologies enable assay of large numbers of lipid analytes, perform high-resolution spatial measurements, or permit highly sensitive lipid assays in single cells. Covered in this review are mass spectrometry, Raman imaging, and fluorescence-based assays including microscopy and microseparations.
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Affiliation(s)
- Ming Yao
- Department of Bioengineering, University of Washington, Seattle, Washington, USA; , ,
| | | | - Nancy L Allbritton
- Department of Bioengineering, University of Washington, Seattle, Washington, USA; , ,
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22
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Yin Y, Ren Z, Zhang L, Qin L, Chen L, Liu L, Jia R, Xue K, Liu B, Wang X. In Situ Proteomic Analysis of Herbicide-Resistant Soybean and Hybrid Seeds via Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:7140-7151. [PMID: 37098110 DOI: 10.1021/acs.jafc.3c00301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Transgenic soybean is the commercial crop with the largest cultivation area worldwide. During transgenic soybean cultivation, exogenous genes may be transferred to wild relatives through gene flow, posing unpredictable ecological risks. Accordingly, an environmental risk assessment should focus on fitness changes and underlying mechanisms in hybrids between transgenic and wild soybeans (Glycine soja). Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) was used for in situ detection and imaging of protein changes in the seeds of transgenic herbicide-resistant soybean harboring epsps and pat genes, non-transgenic soybean, wild soybean, and their F2 hybrid. Protein data clearly distinguished wild soybeans, while the F2 seeds had protein characteristics of both parents and were distinguished from wild soybean seeds. Using UPLC-Q-TOF-MS, 22 differentially expressed proteins (DEPs) were identified, including 13 specific to wild soybean. Sucrose synthase and stress response-related DEPs were differentially expressed in parental and offspring. Differences in these may underpin the greater adaptability of the latter. MSI revealed DEP distribution in transgenic, wild, and F2 seeds. Identifying DEPs related to fitness may elucidate mechanisms underlying fitness differences among the studied varieties. Our study shows that MALDI-MSI has the potential to become a visual method for transgenic soybean analysis.
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Affiliation(s)
- Yue Yin
- Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
- Nanjing Agro-Tech Extension and Service Center, Agricultural and Rural Bureau of Nanjing, Nanjing, Jiangsu 210029, China
| | - Zhentao Ren
- College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
| | - Li Zhang
- Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Liang Qin
- College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (State Ethnic Affairs Commission), Centre for Imaging & Systems Biology, Minzu University of China, Beijing 100081, China
| | - Lulu Chen
- College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (State Ethnic Affairs Commission), Centre for Imaging & Systems Biology, Minzu University of China, Beijing 100081, China
| | - Laipan Liu
- Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Ruizong Jia
- Hainan Key Laboratory for Biosafety Monitoring and Molecular Breeding in Off-Season Reproduction Regions, Sanya 572025, China
| | - Kun Xue
- College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
| | - Biao Liu
- Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China
| | - Xiaodong Wang
- College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (State Ethnic Affairs Commission), Centre for Imaging & Systems Biology, Minzu University of China, Beijing 100081, China
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23
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Liu R, Li J, Lan Y, Nguyen TD, Chen YA, Yang Z. Quantifying Cell Heterogeneity and Subpopulations Using Single Cell Metabolomics. Anal Chem 2023; 95:7127-7133. [PMID: 37115510 DOI: 10.1021/acs.analchem.2c05245] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Mass spectrometry (MS) has become an indispensable tool for metabolomics studies. However, due to the lack of applicable experimental platforms, suitable algorithm, software, and quantitative analyses of cell heterogeneity and subpopulations, investigating global metabolomics profiling at the single cell level remains challenging. We combined the Single-probe single cell MS (SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectrometry), to characterize changes of tumor heterogeneity, quantify cell subpopulations, and prioritize the metabolite biomarkers of each subpopulation. As proof of principle studies, two melanoma cancer cell lines, the primary (WM115; with a lower drug resistance) and the metastatic (WM266-4; with a higher drug resistance), were used as models. Our results indicate that after the treatment of the anticancer drug vemurafenib, a new subpopulation emerged in WM115 cells, while the proportion of the existing subpopulations was changed in the WM266-4 cells. In addition, metabolites for each subpopulation can be prioritized. Combining the SCMS experimental technique with a bioinformatics tool, our label-free approach can be applied to quantitatively study cell heterogeneity, prioritize markers for further investigation, and improve the understanding of cell metabolism in human diseases and response to therapy.
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Affiliation(s)
- Renmeng Liu
- Chemistry and Biochemistry Department, University of Oklahoma, Norman, Oklahoma 73072, United States
| | - Jiannong Li
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, Florida 33647, United States
| | - Yunpeng Lan
- Chemistry and Biochemistry Department, University of Oklahoma, Norman, Oklahoma 73072, United States
| | - Tra D Nguyen
- Chemistry and Biochemistry Department, University of Oklahoma, Norman, Oklahoma 73072, United States
| | - Y Ann Chen
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, Florida 33647, United States
| | - Zhibo Yang
- Chemistry and Biochemistry Department, University of Oklahoma, Norman, Oklahoma 73072, United States
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24
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Gebreyesus ST, Muneer G, Huang CC, Siyal AA, Anand M, Chen YJ, Tu HL. Recent advances in microfluidics for single-cell functional proteomics. LAB ON A CHIP 2023; 23:1726-1751. [PMID: 36811978 DOI: 10.1039/d2lc01096h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.
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Affiliation(s)
- Sofani Tafesse Gebreyesus
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Gul Muneer
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | | | - Asad Ali Siyal
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
| | - Mihir Anand
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
| | - Hsiung-Lin Tu
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
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25
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Hancock SE, Ding E, Johansson Beves E, Mitchell T, Turner N. FACS-assisted single-cell lipidome analysis of phosphatidylcholines and sphingomyelins in cells of different lineages. J Lipid Res 2023; 64:100341. [PMID: 36740022 PMCID: PMC10027561 DOI: 10.1016/j.jlr.2023.100341] [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: 09/26/2022] [Revised: 01/16/2023] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
Recent advances in single-cell genomics and transcriptomics technologies have transformed our understanding of cellular heterogeneity in growth, development, ageing, and disease; however, methods for single-cell lipidomics have comparatively lagged behind in development. We have developed a method for the detection and quantification of a wide range of phosphatidylcholine and sphingomyelin species from single cells that combines fluorescence-assisted cell sorting with automated chip-based nanoESI and shotgun lipidomics. We show herein that our method is capable of quantifying more than 50 different phosphatidylcholine and sphingomyelin species from single cells and can easily distinguish between cells of different lineages or cells treated with exogenous fatty acids. Moreover, our method can detect more subtle differences in the lipidome between cell lines of the same cancer type. Our approach can be run in parallel with other single-cell technologies to deliver near-complete, high-throughput multi-omics data on cells with a similar phenotype and has the capacity to significantly advance our current knowledge on cellular heterogeneity.
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Affiliation(s)
- Sarah E Hancock
- Department of Pharmacology, School of Biomedical Sciences, UNSW Sydney, Australia; Cellular Bioenergetics Laboratory, Victor Chang Cardiac Research Institute, Sydney, NSW, Australia.
| | - Eileen Ding
- Department of Pharmacology, School of Biomedical Sciences, UNSW Sydney, Australia
| | | | - Todd Mitchell
- School of Medicine, University of Wollongong, Wollongong Australia; Molecular Horizons, University of Wollongong, Wollongong Australia
| | - Nigel Turner
- Department of Pharmacology, School of Biomedical Sciences, UNSW Sydney, Australia; Cellular Bioenergetics Laboratory, Victor Chang Cardiac Research Institute, Sydney, NSW, Australia.
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26
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Lewis HM, Gupta P, Saunders KDG, Briones S, von Gerichten J, Townsend PA, Velliou E, Beste DJV, Cexus O, Webb R, Bailey MJ. Nanocapillary sampling coupled to liquid chromatography mass spectrometry delivers single cell drug measurement and lipid fingerprints. Analyst 2023; 148:1041-1049. [PMID: 36723178 PMCID: PMC9969958 DOI: 10.1039/d2an01732f] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 01/27/2023] [Indexed: 01/28/2023]
Abstract
This work describes the development of a new approach to measure drug levels and lipid fingerprints in single living mammalian cells. Nanocapillary sampling is an approach that enables the selection and isolation of single living cells under microscope observation. Here, live single cell nanocapillary sampling is coupled to liquid chromatography for the first time. This allows molecular species to be separated prior to ionisation and improves measurement precision of drug analytes. The efficiency of transferring analytes from the sampling capillary into a vial was optimised in this work. The analysis was carried out using standard flow liquid chromatography coupled to widely available mass spectrometry instrumentation, highlighting opportunities for widespread adoption. The method was applied to 30 living cells, revealing cell-to-cell heterogeneity in the uptake of different drug molecules. Using this system, we detected 14-158 lipid features per single cell, revealing the association between bedaquiline uptake and lipid fingerprints.
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Affiliation(s)
- Holly-May Lewis
- Department of Chemistry, University of Surrey, Guildford, UK.
| | - Priyanka Gupta
- Department of Chemical and Process Engineering, University of Surrey, Guildford, UK
- Centre for 3D Models of Health and Disease, University College London - Division of Surgery and Interventional Science, London, UK
| | | | - Shazneil Briones
- School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | | | - Paul A Townsend
- School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Eirini Velliou
- Department of Chemical and Process Engineering, University of Surrey, Guildford, UK
- Centre for 3D Models of Health and Disease, University College London - Division of Surgery and Interventional Science, London, UK
| | - Dany J V Beste
- School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Olivier Cexus
- School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Roger Webb
- Ion Beam Centre, University of Surrey, Guildford, UK
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27
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Liu Q, Martínez-Jarquín S, Ge W, Zenobi R. Development of a 3D-Printed Ionization Source for Single-Cell Analysis. Anal Chem 2023; 95:1823-1828. [PMID: 36622658 DOI: 10.1021/acs.analchem.2c04279] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Understanding the physiologies and pathologies of diseases requires a thorough understanding of metabolic heterogeneity in cells. This technical note presents a 3D printing technology for manufacturing an ionization source that is specially adapted for mass spectrometry-based single-cell analysis. This all-in-one 3D-printed electrospray ionization source integrates the sample introduction, metabolite extraction, and ionization into one device, simplifying the process of single-cell analysis and improving the reproducibility of the measurement. We successfully used it for high-throughput analysis of three types of cancer cells (around 17 cells/min) and used the t-distributed stochastic neighbor embedding algorithm to distinguish different cell types based on detected metabolites. By simply adjusting the printing parameters of the 3D-printed ionization source, it can be applied to cells with different sizes. The proposed 3D-printed ionization source promises to open new possibilities for single-cell analysis.
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Affiliation(s)
- Qinlei Liu
- Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich CH-8093, Switzerland
| | | | - Wenjie Ge
- Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland
| | - Renato Zenobi
- Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich CH-8093, Switzerland
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28
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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] [Grants] [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
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29
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Václavek T, Foret F. Microfluidic device integrating single-cell extraction and electrical lysis for mass spectrometry detection of intracellular compounds. Electrophoresis 2023; 44:313-322. [PMID: 35315940 DOI: 10.1002/elps.202100379] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/26/2022] [Accepted: 01/28/2022] [Indexed: 02/01/2023]
Abstract
Analysis of cellular composition and metabolism at a single-cell resolution allows gaining more information about complex relationships of cells within tissues or whole living organisms by resolving the variance stemming from the cellular heterogeneity. Mass spectrometry (MS) is a perfect analytical tool satisfying the demanding requirements of detecting and identifying compounds present in such ultralow-volume samples of high chemical complexity. However, the method of sampling and sample ionization is crucial in obtaining relevant information. In this work, we present a microfluidic sampling platform that integrates single-cell extraction from MS-incompatible media with electrical cell lysis and nanoESI-MS analysis of human erythrocytes. Hemoglobin alpha and beta chains (300 amol/cell) were successfully identified in mass spectra of single-erythrocyte lysates.
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Affiliation(s)
- Tomáš Václavek
- Department of Bioanalytical Instrumentation, Institute of Analytical Chemistry of the CAS, Brno, Czech Republic.,Department of Biochemistry, Masaryk University, Brno, Czech Republic
| | - František Foret
- Department of Bioanalytical Instrumentation, Institute of Analytical Chemistry of the CAS, Brno, Czech Republic
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30
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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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31
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Cui H, Wu Q, Zhao Z, Wang Y, Lu H. Selective Capture-Based Single-Cell Mass Spectrometry for Enhancing Sphingolipid Profiling of Neurons with Differentiation of Cell Body from Synapse. Anal Chem 2022; 94:15729-15737. [DOI: 10.1021/acs.analchem.2c03336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Hao Cui
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P.R. China
| | - Qian Wu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P.R. China
| | - Zhihao Zhao
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P.R. China
| | - Yang Wang
- Laboratory of Ethnopharmacology, Institute of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Hunan, Changsha 410008, P.R. China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P.R. China
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32
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Ali A, Davidson S, Fraenkel E, Gilmore I, Hankemeier T, Kirwan JA, Lane AN, Lanekoff I, Larion M, McCall LI, Murphy M, Sweedler JV, Zhu C. Single cell metabolism: current and future trends. Metabolomics 2022; 18:77. [PMID: 36181583 PMCID: PMC10063251 DOI: 10.1007/s11306-022-01934-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 09/05/2022] [Indexed: 11/29/2022]
Abstract
Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.
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Affiliation(s)
- Ahmed Ali
- Leiden Academic Centre for Drug Research, University of Leiden, Gorlaeus Building Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Shawn Davidson
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Ernest Fraenkel
- Department of Biological Engineering and the Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ian Gilmore
- National Physical Laboratory, Teddington, TW11 0LW, Middlesex, UK
| | - Thomas Hankemeier
- Leiden Academic Centre for Drug Research, University of Leiden, Room number GW4.07, Gorlaeus Building, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Jennifer A Kirwan
- Berlin Institute of Health, Metabolomics Platform, Translational Research Unit of the Charite-Universitätsmedizin Berlin, Anna-Louisa-Karsch-Str 2, 10178, Berlin, Germany
| | - Andrew N Lane
- Department of Toxicology and Cancer Biology, and Center for Environmental and Systems Biochemistry, University of Kentucky, 789 S. Limestone St, Lexington, KY, 40536, USA.
| | - Ingela Lanekoff
- Department of Chemistry-BMC, Uppsala University, Husargatan 3 (576), 751 23, Uppsala, Sweden
| | - Mioara Larion
- Center for Cancer Research, National Cancer Institute, Building 37, Room 1136A, Bethesda, MD, 20892, USA
| | - Laura-Isobel McCall
- Department of Chemistry & Biochemistry, Department of Microbiology and Plant Biology, Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, 101 Stephenson Parkway, room 3750, Norman, OK, 73019-5251, USA
| | - Michael Murphy
- Departments of Biological Engineering, Department of Electrical Engineering, and Computer Science and the Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, USA
| | - Jonathan V Sweedler
- Department of Chemistry, and the Beckman Institute, University of Illinois Urbana-Champaign, 505 South Mathews Avenue, Urbana, IL, 61801, USA
| | - Caigang Zhu
- Department of Biomedical Engineering, University of Kentucky, Lexington, KY, 40536, USA
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33
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Chan-Andersen PC, Romanova EV, Rubakhin SS, Sweedler JV. Profiling 26,000 Aplysia californica neurons by single cell mass spectrometry reveals neuronal populations with distinct neuropeptide profiles. J Biol Chem 2022; 298:102254. [PMID: 35835221 PMCID: PMC9396074 DOI: 10.1016/j.jbc.2022.102254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/03/2022] [Accepted: 07/07/2022] [Indexed: 11/30/2022] Open
Abstract
Neuropeptides are a chemically diverse class of cell-to-cell signaling molecules that are widely expressed throughout the central nervous system, often in a cell-specific manner. While cell-to-cell differences in neuropeptides is expected, it is often unclear how exactly neuropeptide expression varies among neurons. Here we created a microscopy-guided, high-throughput single cell matrix-assisted laser desorption/ionization mass spectrometry approach to investigate the neuropeptide heterogeneity of individual neurons in the central nervous system of the neurobiological model Aplysia californica, the California sea hare. In all, we analyzed more than 26,000 neurons from 18 animals and assigned 866 peptides from 66 prohormones by mass matching against an in silico peptide library generated from known Aplysia prohormones retrieved from the UniProt database. Louvain-Jaccard (LJ) clustering of mass spectra from individual neurons revealed 40 unique neuronal populations, or LJ clusters, each with a distinct neuropeptide profile. Prohormones and their related peptides were generally found in single cells from ganglia consistent with the prohormones' previously known ganglion localizations. Several LJ clusters also revealed the cellular colocalization of behaviorally related prohormones, such as an LJ cluster exhibiting achatin and neuropeptide Y, which are involved in feeding, and another cluster characterized by urotensin II, small cardiac peptide, sensorin A, and FRFa, which have shown activity in the feeding network or are present in the feeding musculature. This mass spectrometry-based approach enables the robust categorization of large cell populations based on single cell neuropeptide content and is readily adaptable to the study of a range of animals and tissue types.
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Affiliation(s)
- Peter C Chan-Andersen
- Department of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Elena V Romanova
- Department of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Stanislav S Rubakhin
- Department of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Jonathan V Sweedler
- Department of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
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34
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Nguyen TD, Lan Y, Kane SS, Haffner JJ, Liu R, McCall LI, Yang Z. Single-Cell Mass Spectrometry Enables Insight into Heterogeneity in Infectious Disease. Anal Chem 2022; 94:10567-10572. [PMID: 35863111 PMCID: PMC10064790 DOI: 10.1021/acs.analchem.2c02279] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Cellular heterogeneity is generally overlooked in infectious diseases. In this study, we investigated host cell heterogeneity during infection with Trypanosoma cruzi (T. cruzi) parasites, causative agents of Chagas disease (CD). In chronic-stage CD, only a few host cells are infected with a large load of parasites and symptoms may appear at sites distal to parasite colonization. Furthermore, recent work has revealed T. cruzi heterogeneity with regard to replication rates and drug susceptibility. However, the role of cellular-level metabolic heterogeneity in these processes has yet to be assessed. To fill this knowledge gap, we developed a Single-probe SCMS (single-cell mass spectrometry) method compatible with biosafety protocols, to acquire metabolomics data from individual cells during T. cruzi infection. This study revealed heterogeneity in the metabolic response of the host cells to T. cruzi infection in vitro. Our results showed that parasite-infected cells possessed divergent metabolism compared to control cells. Strikingly, some uninfected cells adjacent to infected cells showed metabolic impacts as well. Specific metabolic changes include increases in glycerophospholipids with infection. These results provide novel insight into the pathogenesis of CD. Furthermore, they represent the first application of bioanalytical SCMS to the study of mammalian-infectious agents, with the potential for broad applications to study infectious diseases.
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Affiliation(s)
- Tra D Nguyen
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Yunpeng Lan
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Shelley S Kane
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Jacob J Haffner
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, Oklahoma 73019, United States.,Department of Anthropology, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Renmeng Liu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Laura-Isobel McCall
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.,Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, Oklahoma 73019, United States.,Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
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35
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Chen X, Peng Z, Yang Z. Metabolomics studies of cell-cell interactions using single cell mass spectrometry combined with fluorescence microscopy. Chem Sci 2022; 13:6687-6695. [PMID: 35756524 PMCID: PMC9172575 DOI: 10.1039/d2sc02298b] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 05/15/2022] [Indexed: 11/21/2022] Open
Abstract
Cell-cell interactions are critical for transmitting signals among cells and maintaining their normal functions from the single-cell level to tissues. In cancer studies, interactions between drug-resistant and drug-sensitive cells play an important role in the development of chemotherapy resistance of tumors. As metabolites directly reflect the cell status, metabolomics studies provide insight into cell-cell communication. Mass spectrometry (MS) is a powerful tool for metabolomics studies, and single cell MS (SCMS) analysis can provide unique information for understanding interactions among heterogeneous cells. In the current study, we utilized a direct co-culture system (with cell-cell contact) to study metabolomics of single cells affected by cell-cell interactions in their living status. A fluorescence microscope was utilized to distinguish these two types of cells for SCMS metabolomics studies using the Single-probe SCMS technique under ambient conditions. Our results show that through interactions with drug-resistant cells, drug-sensitive cancer cells acquired significantly increased drug resistance and exhibited drastically altered metabolites. Further investigation found that the increased drug resistance was associated with multiple metabolism regulations in drug-sensitive cells through co-culture such as the upregulation of sphingomyelins lipids and lactic acid and the downregulation of TCA cycle intermediates. The method allows for direct MS metabolomics studies of individual cells labeled with fluorescent proteins or dyes among heterogeneous populations.
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Affiliation(s)
- Xingxiu Chen
- Chemistry and Biochemistry Department, University of Oklahoma Norman Oklahoma 73072 USA
| | - Zongkai Peng
- Chemistry and Biochemistry Department, University of Oklahoma Norman Oklahoma 73072 USA
| | - Zhibo Yang
- Chemistry and Biochemistry Department, University of Oklahoma Norman Oklahoma 73072 USA
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36
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Sun M, Chen X, Yang Z. Single cell mass spectrometry studies reveal metabolomic features and potential mechanisms of drug-resistant cancer cell lines. Anal Chim Acta 2022; 1206:339761. [PMID: 35473873 PMCID: PMC9046687 DOI: 10.1016/j.aca.2022.339761] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 03/18/2022] [Accepted: 03/22/2022] [Indexed: 12/28/2022]
Abstract
Irinotecan (Iri) is a key drug to treat metastatic colorectal cancer, but its clinical activity is often limited by de novo and acquired drug resistance. Studying the underlying mechanisms of drug resistance is necessary for developing novel therapeutic strategies. In this study, we used both regular and irinotecan-resistant (Iri-resistant) colorectal cell lines as models, and performed single cell mass spectrometry (SCMS) metabolomics studies combined with analyses from cytotoxicity assay, western blot, flow cytometry, quantitative real-time polymerase chain reaction (qPCR), and reactive oxygen species (ROS). Our SCMS results indicate that Iri-resistant cancer cells possess higher levels of unsaturated lipids compared with the regular cancer cells. In addition, multiple protein biomarkers and their corresponding mRNAs of colon cancer stem cells are overexpressed in Iri-resistance cells. Particularly, stearoyl-CoA desaturase 1 (SCD1) is upregulated with the development of drug resistance in Iri-resistant cells, whereas inhibiting the activity of SCD1 efficiently increase their sensitivity to Iri treatment. In addition, we demonstrated that SCD1 directly regulates the expression of ALDH1A1, which contributes to the cancer stemness and ROS level in Iri-resistant cell lines.
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37
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Shakoor A, Gao W, Zhao L, Jiang Z, Sun D. Advanced tools and methods for single-cell surgery. MICROSYSTEMS & NANOENGINEERING 2022; 8:47. [PMID: 35502330 PMCID: PMC9054775 DOI: 10.1038/s41378-022-00376-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 03/21/2022] [Accepted: 03/22/2022] [Indexed: 06/14/2023]
Abstract
Highly precise micromanipulation tools that can manipulate and interrogate cell organelles and components must be developed to support the rapid development of new cell-based medical therapies, thereby facilitating in-depth understanding of cell dynamics, cell component functions, and disease mechanisms. This paper presents a literature review on micro/nanomanipulation tools and their control methods for single-cell surgery. Micromanipulation methods specifically based on laser, microneedle, and untethered micro/nanotools are presented in detail. The limitations of these techniques are also discussed. The biological significance and clinical applications of single-cell surgery are also addressed in this paper.
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Affiliation(s)
- Adnan Shakoor
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Wendi Gao
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, The School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Libo Zhao
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, The School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Zhuangde Jiang
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, The School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Dong Sun
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- State Key Laboratory for Manufacturing Systems Engineering, International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies, The School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
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38
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Abouleila Y, Ali A, Masuda K, Mashaghi A, Shimizu Y. Capillary microsampling-based single-cell metabolomics by mass spectrometry and its applications in medicine and drug discovery. Cancer Biomark 2022; 33:437-447. [DOI: 10.3233/cbm-210184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Characterization of cellular metabolic states is a technical challenge in biomedicine. Cellular heterogeneity caused by inherent diversity in expression of metabolic enzymes or due to sensitivity of metabolic reactions to perturbations, necessitates single cell analysis of metabolism. Heterogeneity is typically seen in cancer and thus, single-cell metabolomics is expectedly useful in studying cancer progression, metastasis, and variations in cancer drug response. However, low sample volumes and analyte concentrations limit detection of critically important metabolites. Capillary microsampling-based mass spectrometry approaches are emerging as a promising solution for achieving single-cell omics. Herein, we focus on the recent advances in capillary microsampling-based mass spectrometry techniques for single-cell metabolomics. We discuss recent technical developments and applications to cancer medicine and drug discovery.
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Affiliation(s)
- Yasmine Abouleila
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Research Center, Misr International University, Cairo, Egypt
| | - Ahmed Ali
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Research Center, Misr International University, Cairo, Egypt
| | - Keiko Masuda
- RIKEN Center for Biosystems Dynamics Research, Osaka, Japan
| | - Alireza Mashaghi
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
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39
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Chen X, Sun M, Yang Z. Single cell mass spectrometry analysis of drug-resistant cancer cells: Metabolomics studies of synergetic effect of combinational treatment. Anal Chim Acta 2022; 1201:339621. [PMID: 35300794 PMCID: PMC8933618 DOI: 10.1016/j.aca.2022.339621] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 01/30/2022] [Accepted: 02/14/2022] [Indexed: 12/24/2022]
Abstract
Irinotecan (IRI), a topoisomerase I inhibitor blocking DNA synthesis, is a widely used chemotherapy drug for metastatic colorectal cancer. Despite being an effective chemotherapy drug, its clinical effectiveness is limited by both intrinsic and acquired drug resistance. Previous studies indicate IRI induces cancer stemness in irinotecan-resistant (IRI-resistant) cells. Metformin, an oral antidiabetic drug, was recently reported for anticancer effects, likely due to its selective killing of cancer stem cells (CSCs). Given IRI-resistant cells exhibiting high cancer stemness, we hypothesize metformin can sensitize IRI-resistant cells and rescue the therapeutic effect. In this work, we utilized the Single-probe mass spectrometry technique to analyze live IRI-resistant cells under different treatment conditions. We discovered that metformin treatment was associated with the downregulation of lipids and fatty acids, potentially through the inhibition of fatty acid synthase (FASN). Importantly, certain species can be only detected from cells in their living status. The level of synergistic effect of metformin and IRI in their co-treatment of IRI-resistant cells was evaluated using Chou-Talalay combinational index. Using enzymatic activity assay, we determined that the co-treatment exhibit the highest FASN inhibition compared with the mono-treatment of IRI or metformin. To our knowledge, this is the first single-cell MS metabolomics study demonstrating metformin-IRI synergistic effect overcoming drug resistance in IRI-resistant cells.
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40
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Song L, Chingin K, Wang M, Zhong D, Chen H, Xu J. Polarity-Specific Profiling of Metabolites in Single Cells by Probe Electrophoresis Mass Spectrometry. Anal Chem 2022; 94:4175-4182. [PMID: 35235307 DOI: 10.1021/acs.analchem.1c03997] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Sensitive analysis of metabolites in a single cell is of fundamental significance for the better understanding of biological variability, differential susceptibility in disease therapy, and cell-to-cell heterogeneity as well. Herein, polarity-specific profiling of metabolites in a single cell was implemented by probe electrophoresis mass spectrometry (PEMS), which combined electrophoresis sampling of metabolites from a single cell and nanoelectrospray ionization-mass spectrometry (nanoESI-MS) analysis of the sampled metabolites. Enhanced extraction of either negatively or positively charged metabolites from a single cell was achieved by applying a DC voltage offset of +2.0 and -2.0 V to the probe, respectively. The experimental data demonstrated that PEMS features high throughput (≥200 peaks) and high sensitivity (≥10-times signal enhancement for [Choline + H]+, [Glutamine + H]+, [Arginine + H]+, etc.) in comparison with direct nanoESI-MS analysis. The biological effects of CdSe quantum dots (QDs) and γ-radiation on Allium cepa cells were investigated by PEMS, which revealed that CdSe QDs lead to the increase of intracellular amines while γ-radiation causes the decrease of intracellular acids. Therefore, this work provides an alternative platform to probe novel insights of cells by sensitive analysis of polarity-specific metabolites in a single cell.
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Affiliation(s)
- Lili Song
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, People's Republic of China
| | - Konstantin Chingin
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, People's Republic of China
| | - Meng Wang
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, People's Republic of China
| | - Dacai Zhong
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, People's Republic of China
| | - Huanwen Chen
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, People's Republic of China
| | - Jiaquan Xu
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, People's Republic of China
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41
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Wei D, Xu M, Wang Z, Tong J. The Development of Single-Cell Metabolism and Its Role in Studying Cancer Emergent Properties. Front Oncol 2022; 11:814085. [PMID: 35083160 PMCID: PMC8784738 DOI: 10.3389/fonc.2021.814085] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 12/16/2021] [Indexed: 12/13/2022] Open
Abstract
Metabolic reprogramming is one of the hallmarks of malignant tumors, which provides energy and material basis for tumor rapid proliferation, immune escape, as well as extensive invasion and metastasis. Blocking the energy and material supply of tumor cells is one of the strategies to treat tumor, however tumor cell metabolic heterogeneity prevents metabolic-based anti-cancer treatment. Therefore, searching for the key metabolic factors that regulate cell cancerous change and tumor recurrence has become a major challenge. Emerging technology––single-cell metabolomics is different from the traditional metabolomics that obtains average information of a group of cells. Single-cell metabolomics identifies the metabolites of single cells in different states by mass spectrometry, and captures the molecular biological information of the energy and substances synthesized in single cells, which provides more detailed information for tumor treatment metabolic target screening. This review will combine the current research status of tumor cell metabolism with the advantages of single-cell metabolomics technology, and explore the role of single-cell sequencing technology in searching key factors regulating tumor metabolism. The addition of single-cell technology will accelerate the development of metabolism-based anti-cancer strategies, which may greatly improve the prognostic survival rate of cancer patients.
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Affiliation(s)
- Dingju Wei
- School of Life Science, Central China Normal University, Wuhan, China
| | - Meng Xu
- School of Life Science, Central China Normal University, Wuhan, China
| | - Zhihua Wang
- Shenzhen Key Laboratory of Cardiovascular Disease, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, China.,State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jingjing Tong
- School of Life Science, Central China Normal University, Wuhan, China
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42
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Tian X, Zou Z, Yang Z. Extract Metabolomic Information from Mass Spectrometry Images Using Advanced Data Analysis. Methods Mol Biol 2022; 2437:253-272. [PMID: 34902154 DOI: 10.1007/978-1-0716-2030-4_18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Mass spectrometry imaging (MSI) data generally contains large sizes and high-dimensional structures due to their inherent complex chemical and spatial information. A variety of data analysis methods have been developed to comprehensively analyze the MSI experimental results and extract essential information. Here, we describe the protocols of data preprocessing and emerging methods for data analyses, including multivariate analysis, machine learning, and image fusion, that have been applied to the data generated from the Single-probe MSI technique. These strategies and methods can be potentially applied to handling data produced from other MSI techniques.
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Affiliation(s)
- Xiang Tian
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA
- Dynamic Omics, Center of Genomics Research (CGR), R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Zhu Zou
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA.
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43
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Chen B, Vavrek M, Cancilla MT, Kertesz V. Development and Application of DropletProbe Mass Spectrometry for Examining Biodistribution of Therapeutics. Methods Mol Biol 2022; 2437:171-180. [PMID: 34902148 DOI: 10.1007/978-1-0716-2030-4_12] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
dropletProbe mass spectrometry is a novel technique for molecular characterization of surfaces. It can be used for rapid ex vivo analysis of therapeutics from thin animal tissue sections and has been shown to improve understanding of a drug's absorption, distribution, metabolism and excretion (ADME) properties. Here, we describe the tissue distribution analysis of diclofenac from a dosed whole-body mouse thin tissue section using a dropletProbe mass spectrometry system.
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Affiliation(s)
- Bingming Chen
- Department of Preclinical Development, Merck & Co., Inc., Kenilworth, NJ, USA.
| | - Marissa Vavrek
- Department of Preclinical Development, Merck & Co., Inc., Kenilworth, NJ, USA
| | - Mark T Cancilla
- Department of Preclinical Development, Merck & Co., Inc., Kenilworth, NJ, USA
| | - Vilmos Kertesz
- Bioanalytical Mass Spectrometry Group, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
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44
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Abstract
Mass spectrometry imaging (MSI) could provide chemical spatial distribution within a diverse range of samples, but absolute quantitation with those techniques is still challenging. Recent years, ambient liquid extraction-based MSI techniques, such as liquid microjunction surface sampling (LMJSS), have been largely developed and were found to be favorable to quantitation by directly doping standards in the extraction solvent. Here, we describe the detailed experimental protocols and the data processing methods for quantitative MSI with LMJSS. The new methods could have absolute quantitative MSI of both endogenous lipids and small metabolites from tissue samples.
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Affiliation(s)
- Qian Wu
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, P. R. China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, P. R. China.
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45
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Xu ST, Yang C, Yan XP. Nanothorn Filter-Facilitated Online Cell Lysis for Rapid and Deep Intracellular Profiling by Single-Cell Mass Spectrometry. Anal Chem 2021; 93:15677-15686. [PMID: 34784185 DOI: 10.1021/acs.analchem.1c03529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Mass spectrometry combined with flow cytometry is emerging for high-throughput single-cell metabolite analysis but still has problems with limited intracellular information coverage. Here, we show a simple and efficient all-in-one system integrating cell injection, cell extraction, online cell lysis, analyte ionization, and mass spectrometric detection for rapid single-HeLa-cell screening with in-depth profiling of cellular metabolites and drugs. Zinc oxide nanothorn-decorated filters with three bore sizes (5.22, 8.36, and 16.75 μm) were fabricated for efficient online lysis of the cell membrane (even nuclear membrane) to facilitate intracellular analyte release and demonstrated to have a size effect for potential subcellular discrimination. The two smaller-bore filters gave 2-11-fold improvements in signal response for representative intracellular metabolites, such as adenosine, glutamine, and leucine/isoleucine. Especially, the smallest-bore filter enabled successful detection of the metabolites in the nucleus, including tetrahydrobiopterin and cyclic guanosine monophosphate. The developed all-in-one system was explored to monitor the uptake of four anticancer drugs, including 5-fluorouracil, doxorubicin, gambogic acid, and paclitaxel in single cells, and further to investigate the drug uptake trends at the subcellular level. The all-in-one system integrates the merits of high-throughput single-cell screening and in-depth intracellular information profiling and is promising for high-coverage single-cell metabolome analysis to serve cell biology research and cancer research.
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Affiliation(s)
- Shu-Ting Xu
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China.,International Joint Laboratory on Food Safety, Wuxi 214122, China.,Institute of Analytical Food Safety, School of Food Science and Technology, Jiangnan University, Wuxi 214122, China.,Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Cheng Yang
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China.,International Joint Laboratory on Food Safety, Wuxi 214122, China.,Institute of Analytical Food Safety, School of Food Science and Technology, Jiangnan University, Wuxi 214122, China.,Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Xiu-Ping Yan
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China.,International Joint Laboratory on Food Safety, Wuxi 214122, China.,Institute of Analytical Food Safety, School of Food Science and Technology, Jiangnan University, Wuxi 214122, China.,Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, Jiangnan University, Wuxi 214122, China
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46
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Recent Advances of Ambient Mass Spectrometry Imaging and Its Applications in Lipid and Metabolite Analysis. Metabolites 2021; 11:metabo11110780. [PMID: 34822438 PMCID: PMC8625079 DOI: 10.3390/metabo11110780] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 11/08/2021] [Accepted: 11/11/2021] [Indexed: 01/02/2023] Open
Abstract
Ambient mass spectrometry imaging (AMSI) has attracted much attention in recent years. As a kind of unlabeled molecular imaging technique, AMSI can enable in situ visualization of a large number of compounds in biological tissue sections in ambient conditions. In this review, the developments of various AMSI techniques are discussed according to one-step and two-step ionization strategies. In addition, recent applications of AMSI for lipid and metabolite analysis (from 2016 to 2021) in disease diagnosis, animal model research, plant science, drug metabolism and toxicology research, etc., are summarized. Finally, further perspectives of AMSI in spatial resolution, sensitivity, quantitative ability, convenience and software development are proposed.
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47
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Luo S, Wu Q, Li Y, Lu H. Per-pixel absolute quantitation for mass spectrometry imaging of endogenous lipidomes by model prediction of mass transfer kinetics in single-probe-based ambient liquid extraction. Talanta 2021; 234:122654. [PMID: 34364463 DOI: 10.1016/j.talanta.2021.122654] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/21/2021] [Accepted: 06/22/2021] [Indexed: 10/21/2022]
Abstract
With the development of mass spectrometry imaging (MSI), techniques providing quantitative information on the spatial distribution have attracted more attentions recent years. However, for MSI of endogenous compounds in bio-samples, the uncertainty of locally varied sampling efficiencies always hinders accurate absolute quantitation. Here single-probe was used for ambient liquid extraction MSI in rat cerebellum, and standards of phosphatidylcholines (PCs) and cerebrosides (CBs) were doped in extraction solvent. The extraction kinetic curves of endogenous lipids in the ambient liquid extraction during probe parking in single pixel of tissue were investigated. From the results, the extraction kinetic curves were varied between different lipid species in different brain regions, resulting in variations of extraction efficiencies between imaging pixels, and calibration with standards deposited in tissue could not compensate for the variations. In our approach, the theoretical kinetic model of ambient liquid extraction was established, and original concentrations of endogenous lipids in each pixel of tissue were predicted by fitting the experimental extraction kinetic curve in each imaging pixel to the model. The experimental data was demonstrated to be well fitted to the kinetic model with R2 > 0.86, and only with 18-s extraction in each pixel, the original lipid concentrations were predicted accurately with relative errors <23%. With the new method, totally 157 lipids and small metabolites were imaged, and per-pixel quantitation was achieved for 19 PCs and 4 CBs. Compared with conventional quantitative MSI (q-MSI) method, the new q-MSI method had better reproducibility and wider linear range, and produced better contrast in the quantitative images of lipids in brain tissue with less hot spots and noises. The absolute quantitation results by the new method were verified by quantitative LC-MS method with Pearson'r > 0.9 and the slope of the linear fitting line of the correlation plot near 1.
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Affiliation(s)
- Shifen Luo
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, 410083, PR China
| | - Qian Wu
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, 410083, PR China.
| | - Youmei Li
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, 410083, PR China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Changsha, Hunan, 410083, PR China
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48
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Simon D, Oleschuk R. The liquid micro junction-surface sampling probe (LMJ-SSP); a versatile ambient mass spectrometry interface. Analyst 2021; 146:6365-6378. [PMID: 34553725 DOI: 10.1039/d1an00725d] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Ambient ionization methods have become important tools in mass spectrometry. The LMJ-SSP can significantly simplify/reduce lengthy sample preparation requirements associated with mass spectrometry analysis. Samples may be introduced through direct contact, insertion and droplet injection, enabling applications from drug discovery and surface analysis to tissue profiling and metabolic mapping. This review examines the underlying principles associated with the LMJ-SSP interface and highlights modifications of the original design that have extended its capability. We summarize different application areas that have exploited the method and describe potential future directions for the adaptable ambient ionization source.
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Affiliation(s)
- David Simon
- Department of Chemistry, Queen's University, Kingston, Ontario, K7L 3N6, Canada.
| | - Richard Oleschuk
- Department of Chemistry, Queen's University, Kingston, Ontario, K7L 3N6, Canada.
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49
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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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50
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Liu Z, Ulrich vonBargen R, McCall LI. Central role of metabolism in Trypanosoma cruzi tropism and Chagas disease pathogenesis. Curr Opin Microbiol 2021; 63:204-209. [PMID: 34455304 PMCID: PMC8463485 DOI: 10.1016/j.mib.2021.07.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 07/19/2021] [Accepted: 07/21/2021] [Indexed: 01/17/2023]
Abstract
Chagas disease is a neglected tropical disease caused by Trypanosoma cruzi parasites. During mammalian infection, T. cruzi alternates between an intracellular stage and extracellular stage. T. cruzi adapts its metabolism to this lifestyle, while also reshaping host metabolic pathways. Such host metabolic adaptations compensate for parasite-induced stress, but may promote parasite survival and proliferation. Recent work has demonstrated that metabolism controls parasite tropism and location of Chagas disease symptoms, and regulates whether infection is mild or severe. Such findings have important translational applications with regards to treatment and diagnostic test development, though further research is needed with regards to in vivo parasite metabolic gene expression, relationship between magnitude of local metabolic perturbation, parasite strain and disease location, and host-parasite-microbiota co-metabolism.
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Affiliation(s)
- Zongyuan Liu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, 73019, United States; Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, Oklahoma, 73019, United States
| | - Rebecca Ulrich vonBargen
- Department of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, 73019, United States
| | - Laura-Isobel McCall
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, 73019, United States; Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, Oklahoma, 73019, United States; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, 73019, United States.
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