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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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2
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Sun F, Li H, Sun D, Fu S, Gu L, Shao X, Wang Q, Dong X, Duan B, Xing F, Wu J, Xiao M, Zhao F, Han JDJ, Liu Q, Fan X, Li C, Wang C, Shi T. Single-cell omics: experimental workflow, data analyses and applications. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-023-2561-0. [PMID: 39060615 DOI: 10.1007/s11427-023-2561-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/18/2024] [Indexed: 07/28/2024]
Abstract
Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
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Affiliation(s)
- Fengying Sun
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China
| | - Haoyan Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Dongqing Sun
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Shaliu Fu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Lei Gu
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Shao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China
| | - Qinqin Wang
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Dong
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Bin Duan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Feiyang Xing
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Jun Wu
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Minmin Xiao
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Qi Liu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China.
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China.
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China.
- Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
| | - Chen Li
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Chenfei Wang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Tieliu Shi
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
- Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai, 200062, China.
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Yao H, Yang J, Wang Z, Pan X, Pan J, Li H, Zhang S. High-Throughput Metabolite Analysis of Unicellular Microalgae by Orthogonal Hybrid Ionization Label-Free Mass Cytometry. Anal Chem 2024; 96:11404-11411. [PMID: 38960896 DOI: 10.1021/acs.analchem.4c01541] [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: 07/05/2024]
Abstract
Microalgae metabolite analysis is fundamental for the rational design of metabolic engineering strategies for the biosynthesis of high-value products. Mass spectrometry (MS) has been utilized for single-cell microalgae analysis. However, limitations in the detection throughput and polarities of detectable substances make it difficult to realize high-throughput screening of high-performance microalgae. Herein, a plasma-assisted label-free mass cytometry, named as PACyESI-MS, was proposed combining the advantages of orthogonal hybrid ionization and high-throughput MS analysis, which realized rapid metabolite detection of single microalgae. The cell detection throughput of PACyESI-MS was up to 52 cells/min. Dozens of the critical primary and secondary metabolites within single microalgae were detected simultaneously, including pigments, lipids, and energy metabolites. Furthermore, metabolite changes of Chlamydomonas reinhardtii and Haematococcus pluvialis under nitrogen deficiency stress were studied. Discrimination of Chlamydomonas under different nutrient conditions was realized using single-cell metabolite profiles obtained by PACyESI-MS. The relationships between the accumulation of bioactive astaxanthin and changes in functional primary metabolites of Haematococcus were investigated. It was demonstrated that PACyESI-MS can detect the flexible change of metabolites in single microalgae cells under different nutritional conditions and during the synthesis of high-value products, which is expected to become an important tool for the design of metabolic engineering-based high-performance microalgae factories.
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Affiliation(s)
- Huan Yao
- National Institute of Metrology, Beijing 100029, China
- Key Laboratory of Chemical Metrology and Applications on Nutrition and Health for State Market Regulation, Beijing 100029, China
| | - Jinlei Yang
- Department of Chemistry, Tsinghua University, Beijing 100084, P.R. China
| | - Zhengmao Wang
- MOE Key Laboratory of Protein Sciences, School of Life Science, Tsinghua University, Beijing 100084, P.R. China
- Laboratory for Marine Biology and Biotechnology, Qingdao Marine Science and Technology Center, Qingdao, Shandong Province 266000, China
| | - Xingyu Pan
- Department of Chemistry, Tsinghua University, Beijing 100084, P.R. China
| | - Junmin Pan
- MOE Key Laboratory of Protein Sciences, School of Life Science, Tsinghua University, Beijing 100084, P.R. China
- Laboratory for Marine Biology and Biotechnology, Qingdao Marine Science and Technology Center, Qingdao, Shandong Province 266000, China
| | - Hongmei Li
- National Institute of Metrology, Beijing 100029, China
- Key Laboratory of Chemical Metrology and Applications on Nutrition and Health for State Market Regulation, Beijing 100029, China
| | - Sichun Zhang
- Department of Chemistry, Tsinghua University, Beijing 100084, P.R. China
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4
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Colón Rosado J, Sun L. Solid-Phase Microextraction-Aided Capillary Zone Electrophoresis-Mass Spectrometry: Toward Bottom-Up Proteomics of Single Human Cells. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1120-1127. [PMID: 38514245 PMCID: PMC11157658 DOI: 10.1021/jasms.3c00429] [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: 12/13/2023] [Revised: 03/02/2024] [Accepted: 03/13/2024] [Indexed: 03/23/2024]
Abstract
Capillary zone electrophoresis-mass spectrometry (CZE-MS) has been recognized as a valuable technique for the proteomics of mass-limited biological samples (i.e., single cells). However, its broad adoption for single cell proteomics (SCP) of human cells has been impeded by the low sample loading capacity of CZE, only allowing us to use less than 5% of the available peptide material for each measurement. Here we present a reversed-phase-based solid-phase microextraction (RP-SPME)-CZE-MS platform to solve the issue, paving the way for SCP of human cells using CZE-MS. The RP-SPME-CZE system was constructed in one fused silica capillary with zero dead volume for connection via in situ synthesis of a frit, followed by packing C8 beads into the capillary to form a roughly 2 mm long SPME section. Peptides captured by SPME were eluted with a buffer containing 30% (v/v) acetonitrile and 50 mM ammonium acetate (pH 6.5), followed by dynamic pH junction-based CZE-MS. The SPME-CZE-MS enabled the injection of nearly 40% of the available peptide sample for each measurement. The system identified 257 ± 24 proteins and 523 ± 69 peptides (N = 2) using a Q-Exactive HF mass spectrometer when only 0.25 ng of a commercial HeLa cell digest was available in the sample vial and 0.1 ng of the sample was injected. The amount of available peptide is equivalent to the protein mass of one HeLa cell. The data indicate that SPME-CZE-MS is ready for SCP of human cells.
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Affiliation(s)
- Jorge
A. Colón Rosado
- Department of Chemistry, Michigan
State University, 578 S Shaw Lane, East Lansing, Michigan 48824, United States
| | - Liangliang Sun
- Department of Chemistry, Michigan
State University, 578 S Shaw Lane, East Lansing, Michigan 48824, United States
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5
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O'Connor E, Micklefield J, Cai Y. Searching for the optimal microbial factory: high-throughput biosensors and analytical techniques for screening small molecules. Curr Opin Biotechnol 2024; 87:103125. [PMID: 38547587 DOI: 10.1016/j.copbio.2024.103125] [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: 01/18/2024] [Revised: 03/06/2024] [Accepted: 03/07/2024] [Indexed: 06/09/2024]
Abstract
High-throughput screening technologies have been lacking in comparison to the plethora of high-throughput genetic diversification techniques developed in biotechnology. This review explores the challenges and advancements in high-throughput screening for high-value natural products, focusing on the critical need to expand ligand targets for biosensors and increase the throughput of analytical techniques in screening microbial cell libraries for optimal strain performance. The engineering techniques to broaden the scope of ligands for biosensors, such as transcription factors, G protein-coupled receptors and riboswitches are discussed. On the other hand, integration of microfluidics with traditional analytical methods is explored, covering fluorescence-activated cell sorting, Raman-activated cell sorting and mass spectrometry, emphasising recent developments in maximising throughput.
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Affiliation(s)
- Eloise O'Connor
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK
| | - Jason Micklefield
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK
| | - Yizhi Cai
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK.
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6
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Zhu J, Pan S, Chai H, Zhao P, Feng Y, Cheng Z, Zhang S, Wang W. Microfluidic Impedance Cytometry Enabled One-Step Sample Preparation for Efficient Single-Cell Mass Spectrometry. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2310700. [PMID: 38483007 DOI: 10.1002/smll.202310700] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 03/05/2024] [Indexed: 06/27/2024]
Abstract
Single-cell mass spectrometry (MS) is significant in biochemical analysis and holds great potential in biomedical applications. Efficient sample preparation like sorting (i.e., separating target cells from the mixed population) and desalting (i.e., moving the cells off non-volatile salt solution) is urgently required in single-cell MS. However, traditional sample preparation methods suffer from complicated operation with various apparatus, or insufficient performance. Herein, a one-step sample preparation strategy by leveraging label-free impedance flow cytometry (IFC) based microfluidics is proposed. Specifically, the IFC framework to characterize and sort single-cells is adopted. Simultaneously with sorting, the target cell is transferred from the local high-salinity buffer to the MS-compatible solution. In this way, one-step sorting and desalting are achieved and the collected cells can be directly fed for MS analysis. A high sorting efficiency (>99%), cancer cell purity (≈87%), and desalting efficiency (>99%), and the whole workflow of impedance-based separation and MS analysis of normal cells (MCF-10A) and cancer cells (MDA-MB-468) are verified. As a standalone sample preparation module, the microfluidic chip is compatible with a variety of MS analysis methods, and envisioned to provide a new paradigm in efficient MS sample preparation, and further in multi-modal (i.e., electrical and metabolic) characterization of single-cells.
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Affiliation(s)
- Junwen Zhu
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Siyuan Pan
- Department of Chemistry, Tsinghua University, Beijing, 100084, China
| | - Huichao Chai
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Peng Zhao
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Yongxiang Feng
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Zhen Cheng
- Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Sichun Zhang
- Department of Chemistry, Tsinghua University, Beijing, 100084, China
| | - Wenhui Wang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
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7
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Qin S, Zhang Y, Shi M, Miao D, Lu J, Wen L, Bai Y. In-depth organic mass cytometry reveals differential contents of 3-hydroxybutanoic acid at the single-cell level. Nat Commun 2024; 15:4387. [PMID: 38782922 PMCID: PMC11116506 DOI: 10.1038/s41467-024-48865-2] [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: 06/22/2023] [Accepted: 05/16/2024] [Indexed: 05/25/2024] Open
Abstract
Comprehensive single-cell metabolic profiling is critical for revealing phenotypic heterogeneity and elucidating the molecular mechanisms underlying biological processes. However, single-cell metabolomics remains challenging because of the limited metabolite coverage and inability to discriminate isomers. Herein, we establish a single-cell metabolomics platform for in-depth organic mass cytometry. Extended single-cell analysis time guarantees sufficient MS/MS acquisition for metabolite identification and the isomers discrimination while online sampling ensures the high-throughput of the method. The largest number of identified metabolites (approximately 600) are achieved in single cells and fine subtyping of MCF-7 cells is first demonstrated by an investigation on the differential levels of 3-hydroxybutanoic acid among clusters. Single-cell transcriptome analysis reveals differences in the expression of 3-hydroxybutanoic acid downstream antioxidative stress genes, such as metallothionein 2 (MT2A), while a fluorescence-activated cell sorting assay confirms the positive relationship between 3-hydroxybutanoic acid and target proteins; these results suggest that the heterogeneity of 3-hydroxybutanoic acid provides cancer cells with different ability to resist surrounding oxidative stress. Our method paves the way for deep single-cell metabolome profiling and investigations on the physiological and pathological processes that occur during cancer.
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Affiliation(s)
- Shaojie Qin
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Yi Zhang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Mingying Shi
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Daiyu Miao
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Jiansen Lu
- Biomedical Pioneering Innovative Center, School of Life Sciences, Peking University, Beijing, China
| | - Lu Wen
- Biomedical Pioneering Innovative Center, School of Life Sciences, Peking University, Beijing, China
| | - Yu Bai
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.
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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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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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Sun X, Yu Y, Qian K, Wang J, Huang L. Recent Progress in Mass Spectrometry-Based Single-Cell Metabolic Analysis. SMALL METHODS 2024; 8:e2301317. [PMID: 38032130 DOI: 10.1002/smtd.202301317] [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: 09/27/2023] [Revised: 11/10/2023] [Indexed: 12/01/2023]
Abstract
Single-cell analysis enables the measurement of biomolecules at the level of individual cells, facilitating in-depth investigations into cellular heterogeneity and precise interpretation of the related biological mechanisms. Among these biomolecules, cellular metabolites exhibit remarkable sensitivity to environmental and biochemical changes, unveiling a hidden world underlying cellular heterogeneity and allowing for the determination of cell physiological states. However, the metabolic analysis of single cells is challenging due to the extremely low concentrations, substantial content variations, and rapid turnover rates of cellular metabolites. Mass spectrometry (MS), characterized by its high sensitivity, wide dynamic range, and excellent selectivity, is employed in single-cell metabolic analysis. This review focuses on recent advances and applications of MS-based single-cell metabolic analysis, encompassing three key steps of single-cell isolation, detection, and application. It is anticipated that MS will bring profound implications in biomedical practices, serving as advanced tools to depict the single-cell metabolic landscape.
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Affiliation(s)
- Xuming Sun
- Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
- Shanghai Institute of Thoracic Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, 453003, P. R. China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang Medical University, Xinxiang, 453003, P. R. China
- Xinxiang Key Laboratory of Neurobiosensor, Xinxiang Medical University, Xinxiang, 453003, P. R. China
| | - Yi Yu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, 453003, P. R. China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang Medical University, Xinxiang, 453003, P. R. China
- Xinxiang Key Laboratory of Neurobiosensor, Xinxiang Medical University, Xinxiang, 453003, P. R. China
| | - Kun Qian
- School of Biomedical Engineering, Institute of Medical Robotics and Med X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Jiayi Wang
- Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
- Shanghai Institute of Thoracic Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
| | - Lin Huang
- Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
- Shanghai Institute of Thoracic Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
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11
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Yang J, Cheng R, Pan X, Pan S, Du M, Yao H, Hu Z, Zhang S, Zhang X. Single-Cell Unsaturated Lipid Profiling for Studying Chemoresistance Heterogeneity of Triple-Negative Breast Cancer Cells. Anal Chem 2024. [PMID: 38334074 DOI: 10.1021/acs.analchem.3c04887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
Chemoresistance to triple-negative breast cancer (TNBC) is a critical issue in clinical practice. Lipid metabolism takes a unique role in breast cancer cells; especially, unsaturated lipids involving cell membrane fluidity and peroxidation are highly remarked. At present, for the lack of a high-resolution molecular recognition platform at the single-cell level, it is still hard to systematically study chemoresistance heterogeneity based on lipid unsaturation proportion. By designing a single-cell mass spectrometry workflow based on CyESI-MS, we profiled the unsaturated lipids of TNBC cells to evaluate lipidomic remodeling under platinum stress. Profiling revealed the heterogeneity of the polyunsaturated lipid proportion of TNBC cells under cisplatin treatment. A cluster of cells identified by polyunsaturated lipid accumulation was found to be involved in platinum sensitivity. Furthermore, we found that the chemoresistance of TNBC cells could be regulated by fatty acid supplementation, which determinates the composition of unsaturated lipids. These discoveries provide insights for monitoring and controlling cellular unsaturated lipid proportions to overcome chemoresistance in breast cancer.
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Affiliation(s)
- Jinlei Yang
- Department of Chemistry, Tsinghua University, Beijing 100084, China
| | - Runsong Cheng
- Department of Chemistry, Tsinghua University, Beijing 100084, China
| | - Xingyu Pan
- Department of Chemistry, Tsinghua University, Beijing 100084, China
| | - Siyuan Pan
- Department of Chemistry, Tsinghua University, Beijing 100084, China
| | - Murong Du
- Department of Chemistry, Tsinghua University, Beijing 100084, China
| | - Huan Yao
- National Institute of Metrology, Beijing 100029, China
- Key Laboratory of Chemical Metrology and Applications on Nutrition and Health for State Market Regulation, Beijing 100029, China
| | - Zhian Hu
- Beijing Key Laboratory for Bioengineering and Sensing Technology, School of Chemistry and Biological Engineering, University of Science and Technology, Beijing 100083, China
| | - Sichun Zhang
- Department of Chemistry, Tsinghua University, Beijing 100084, China
| | - Xinrong Zhang
- Department of Chemistry, Tsinghua University, Beijing 100084, China
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12
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Pan S, Liu C, Yao H, Pan X, Li J, Yang J, Du M, Liu P, Zhang S, Zhang X. Single-cell metabolite profiling enables information-rich classification of lymphocyte types and subtypes. Chem Commun (Camb) 2024; 60:392-395. [PMID: 38053454 DOI: 10.1039/d3cc05011d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
Lymphocytes play crucial roles in the human immune system; however, detailed metabolite characteristics need to be further investigated. Herein, we propose a lymphocyte classification method based on metabolite profiling at the single-cell level. The percentages of different lymphocyte types were calculated with a low margin of error, confirming that the metabolites could serve as a basis for lymphocyte classification. Furthermore, we analyzed the CD4/CD8 ratio in human peripheral blood to verify the feasibility of this method for the classification of lymphocyte subtypes. The proposed method is expected to be a potential tool for the clinical diagnosis of lymphocyte-related diseases.
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Affiliation(s)
- Siyuan Pan
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China.
| | - Changyi Liu
- State Key Laboratory of Complex, Severe, and Rare Diseases, Peking Union Medical College Hospital, Beijing 100730, P. R. China.
| | - Huan Yao
- Division of Chemical Metrology and Analytical Science, National Institute of Metrology, Beijing 100029, P. R. China
| | - Xingyu Pan
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China.
| | - Jinhang Li
- Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
| | - Jinlei Yang
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China.
| | - Murong Du
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China.
| | - Peng Liu
- State Key Laboratory of Complex, Severe, and Rare Diseases, Peking Union Medical College Hospital, Beijing 100730, P. R. China.
| | - Sichun Zhang
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China.
| | - Xinrong Zhang
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China.
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13
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Zeng Q, Xia MC, Yin X, Cheng S, Xue Z, Tan S, Gong X, Ye Z. Recent developments in ionization techniques for single-cell mass spectrometry. Front Chem 2023; 11:1293533. [PMID: 38130875 PMCID: PMC10733462 DOI: 10.3389/fchem.2023.1293533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/27/2023] [Indexed: 12/23/2023] Open
Abstract
The variation among individual cells plays a significant role in many biological functions. Single-cell analysis is advantageous for gaining insight into intricate biochemical mechanisms rarely accessible when studying tissues as a whole. However, measurement on a unicellular scale is still challenging due to unicellular complex composition, minute substance quantities, and considerable differences in compound concentrations. Mass spectrometry has recently gained extensive attention in unicellular analytical fields due to its exceptional sensitivity, throughput, and compound identification abilities. At present, single-cell mass spectrometry primarily concentrates on the enhancement of ionization methods. The principal ionization approaches encompass nanoelectrospray ionization (nano-ESI), laser desorption ionization (LDI), secondary ion mass spectrometry (SIMS), and inductively coupled plasma (ICP). This article summarizes the most recent advancements in ionization techniques and explores their potential directions within the field of single-cell mass spectrometry.
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Affiliation(s)
- Qingli Zeng
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Hangzhou, China
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Meng-Chan Xia
- National Anti-Drug Laboratory Beijing Regional Center, Beijing, China
| | - Xinchi Yin
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Simin Cheng
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Zhichao Xue
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Siyuan Tan
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Xiaoyun Gong
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Zihong Ye
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Hangzhou, China
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14
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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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15
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Marques C, Friedrich F, Liu L, Castoldi F, Pietrocola F, Lanekoff I. Global and Spatial Metabolomics of Individual Cells Using a Tapered Pneumatically Assisted nano-DESI Probe. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2518-2524. [PMID: 37830184 PMCID: PMC10623638 DOI: 10.1021/jasms.3c00239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 09/26/2023] [Accepted: 09/29/2023] [Indexed: 10/14/2023]
Abstract
Single-cell metabolomics has the potential to reveal unique insights into intracellular mechanisms and biological processes. However, the detection of metabolites from individual cells is challenging due to their versatile chemical properties and concentrations. Here, we demonstrate a tapered probe for pneumatically assisted nanospray desorption electrospray ionization (PA nano-DESI) mass spectrometry that enables both chemical imaging of larger cells and global metabolomics of smaller 15 μm cells. Additionally, by depositing cells in predefined arrays, we show successful metabolomics from three individual INS-1 cells per minute, which enabled the acquisition of data from 479 individual cells. Several cells were used to optimize analytical conditions, and 93 or 97 cells were used to monitor metabolome alterations in INS-1 cells after exposure to a low or high glucose concentration, respectively. Our analytical approach offers insights into cellular heterogeneity and provides valuable information about cellular processes and responses in individual cells.
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Affiliation(s)
- Cátia Marques
- Department
of Chemistry—BMC, Uppsala University, 75123 Uppsala, Sweden
| | - Felix Friedrich
- Department
of Chemistry—BMC, Uppsala University, 75123 Uppsala, Sweden
| | - Liangwen Liu
- Department
of Medical Cell Biology, Uppsala University, 75123 Uppsala, Sweden
| | - Francesca Castoldi
- Department
of Biosciences and Nutrition, Karolinska
Institute, 14152 Huddinge, Sweden
| | - Federico Pietrocola
- Department
of Biosciences and Nutrition, Karolinska
Institute, 14152 Huddinge, Sweden
| | - Ingela Lanekoff
- Department
of Chemistry—BMC, Uppsala University, 75123 Uppsala, Sweden
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16
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Liu F, Wu T, Tian A, He C, Bi X, Lu Y, Yang K, Xia W, Ye J. Intracellular metabolic profiling of drug resistant cells by surface enhanced Raman scattering. Anal Chim Acta 2023; 1279:341809. [PMID: 37827617 DOI: 10.1016/j.aca.2023.341809] [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: 06/26/2023] [Revised: 09/07/2023] [Accepted: 09/08/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND Intracellular metabolic profiling reveals real-time metabolic information useful for the study of underlying mechanisms of cells in particular conditions such as drug resistance. However, mass spectrometry (MS), one of the leading metabolomics technologies, usually requires a large number of cells and complex pretreatments. Surface enhanced Raman scattering (SERS) has an ultrahigh detection sensitivity and specificity, favorable for metabolomics analysis. However, some targeted SERS methods focus on very limited metabolite without global bioprofiling, and some label-free approaches try to fingerprint the metabolic response based on whole SERS spectral classification, but comprehensive interpretation of biological mechanisms was lacking. (95) RESULTS: We proposed a label-free SERS technique for intracellular metabolic profiling in complex cellular lysates within 3 min. We first compared three kinds of cellular lysis methods and sonication lysis shows the highest extraction efficiency of metabolites. To obtain comprehensive metabolic information, we collected a spectral set for each sample and further qualified them by the Pearson correlation coefficient (PCC) to calculate how many spectra should be acquired at least to gain the adequate information from a statistical and global view. In addition, according to our measurements with 10 pure metabolites, we can understand the spectra acquired from complex cellular lysates of different cell lines more precisely. Finally, we further disclosed the variations of 22 SERS bands in enzalutamide-resistant prostate cancer cells and some are associated with the androgen receptor signaling activity and the methionine salvage pathway in the drug resistance process, which shows the same metabolic trends as MS. (149) SIGNIFICANCE: Our technique has the capability to capture the intracellular metabolic fingerprinting with the optimized lysis approach and spectral set collection, showing high potential in rapid, sensitive and global metabolic profiling in complex biosamples and clinical liquid biopsy. This gives a new perspective to the study of SERS in insightful understanding of relevant biological mechanisms. (54).
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Affiliation(s)
- Fugang Liu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China
| | - Tingyu Wu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China
| | - Ao Tian
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China
| | - Chang He
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China
| | - Xinyuan Bi
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China
| | - Yao Lu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China
| | - Kai Yang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China
| | - Weiliang Xia
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China; State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200032, PR China.
| | - Jian Ye
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PR China; State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200032, PR China; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, PR China; Shanghai Key Laboratory of Gynecologic Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, PR China.
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17
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Deng J, Zeng X, He C, Zhong D, Wu Y, Liu N, Luan T, Yang Y. Exploring the Accumulation Behavior and Heterogeneity of Perfluorooctanesulfonic Acid in Zebrafish Primary Organ Cells by Single-Cell Mass Cytometry. Anal Chem 2023; 95:13750-13755. [PMID: 37669419 DOI: 10.1021/acs.analchem.3c02398] [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: 09/07/2023]
Abstract
Perfluorooctanesulfonic acid (PFOS) is a commonly found environmental pollutant with potential toxicity and health risks to biosystems and ecosystems. Study of the accumulation behavior and heterogeneity of PFOS in biological primary organ cells provides us significant insights to explore its cytotoxicity, carcinogenicity, and mutagenicity. Here a single-cell mass cytometry system was established for the high-throughput analysis of trace PFOS and the exploration of its accumulation behavior and heterogeneity in zebrafish primary organ cells. The single-cell mass cytometry system applied a ∼25 μm constant-inner-diameter capillary as the single-cell generation and transportation channel with an etched tip-end of 40 μm as the nanoelectrospray emitter for mass spectrometric analysis. The single-cell mass cytometry system showed satisfactory semiquantitative performance and sensitivity for analysis of PFOS in single cells, with a high detection throughput of ∼35 cells/min. Subsequently, the liver, intestine, heart, and brain from PFOS-exposed zebrafish (100 pg/μL, 28 days) were dissociated and prepared as cell suspensions, and the cell suspensions were introduced into the single-cell mass cytometry system for high-throughput analysis of PFOS in individual primary organ cells. Significant cellular accumulation heterogeneities were observed, with the highest content in liver cells, followed by intestine cells, then heart cells, and the lowest in brain cells. In addition, the dynamics of PFOS in the zebrafish liver, intestine, heart, and brain cells showed typical violin plot distributions and were well-described using a gamma (γ) function.
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Affiliation(s)
- Jiewei Deng
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
- Smart Medical Innovation Technology Center, Guangdong University of Technology, Guangzhou 510006, China
- Guangdong Laboratory of Chemistry and Fine Chemical Engineering Jieyang Center, Jieyang 515200, China
| | - Xiliu Zeng
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
| | - Cai He
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
- Guangdong Provincial Engineering Research Center for Ambient Mass Spectrometry, Guangdong Provincial Key Laboratory of Chemical Measurement and Emergency Test Technology, Institute of Analysis, Guangdong Academy of Sciences, (China National Analytical Center, Guangzhou), 100 Xianlie Middle Road, Guangzhou 510070, China
| | - Dahao Zhong
- Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou 510006, China
| | - Yuehua Wu
- Guangdong Women and Children Hospital, Guangzhou 511400, China
| | - Ning Liu
- Guangdong Provincial Engineering Research Center for Ambient Mass Spectrometry, Guangdong Provincial Key Laboratory of Chemical Measurement and Emergency Test Technology, Institute of Analysis, Guangdong Academy of Sciences, (China National Analytical Center, Guangzhou), 100 Xianlie Middle Road, Guangzhou 510070, China
| | - Tiangang Luan
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
- Guangdong Laboratory of Chemistry and Fine Chemical Engineering Jieyang Center, Jieyang 515200, China
- School of Life Sciences, Sun Yat-Sen University, Guangzhou 510275, China
| | - Yunyun Yang
- Guangdong Provincial Engineering Research Center for Ambient Mass Spectrometry, Guangdong Provincial Key Laboratory of Chemical Measurement and Emergency Test Technology, Institute of Analysis, Guangdong Academy of Sciences, (China National Analytical Center, Guangzhou), 100 Xianlie Middle Road, Guangzhou 510070, China
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18
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Zhang H, Liu Y, Fields L, Shi X, Huang P, Lu H, Schneider AJ, Tang X, Puglielli L, Welham NV, Li L. Single-cell lipidomics enabled by dual-polarity ionization and ion mobility-mass spectrometry imaging. Nat Commun 2023; 14:5185. [PMID: 37626051 PMCID: PMC10457347 DOI: 10.1038/s41467-023-40512-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 07/27/2023] [Indexed: 08/27/2023] Open
Abstract
Single-cell (SC) analysis provides unique insight into individual cell dynamics and cell-to-cell heterogeneity. Here, we utilize trapped ion mobility separation coupled with dual-polarity ionization mass spectrometry imaging (MSI) to enable high-throughput in situ profiling of the SC lipidome. Multimodal SC imaging, in which dual-polarity-mode MSI is used to perform serial data acquisition runs on individual cells, significantly enhanced SC lipidome coverage. High-spatial resolution SC-MSI identifies both inter- and intracellular lipid heterogeneity; this heterogeneity is further explicated by Uniform Manifold Approximation and Projection and machine learning-driven classifications. We characterize SC lipidome alteration in response to stearoyl-CoA desaturase 1 inhibition and, additionally, identify cell-layer specific lipid distribution patterns in mouse cerebellar cortex. This integrated multimodal SC-MSI technology enables high-resolution spatial mapping of intercellular and cell-to-cell lipidome heterogeneity, SC lipidome remodeling induced by pharmacological intervention, and region-specific lipid diversity within tissue.
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Affiliation(s)
- Hua Zhang
- School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, 53705, USA
| | - Yuan Liu
- School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, 53705, USA
| | - Lauren Fields
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Xudong Shi
- Division of Otolaryngology, Department of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, 53792, USA
| | - Penghsuan Huang
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Haiyan Lu
- School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, 53705, USA
| | - Andrew J Schneider
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Xindi Tang
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Luigi Puglielli
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Nathan V Welham
- Division of Otolaryngology, Department of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, 53792, USA
| | - Lingjun Li
- School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, 53705, USA.
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA.
- Lachman Institute for Pharmaceutical Development, School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Wisconsin Center for NanoBioSystems, School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA.
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19
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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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20
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Ayon NJ. High-Throughput Screening of Natural Product and Synthetic Molecule Libraries for Antibacterial Drug Discovery. Metabolites 2023; 13:625. [PMID: 37233666 PMCID: PMC10220967 DOI: 10.3390/metabo13050625] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 04/29/2023] [Accepted: 05/01/2023] [Indexed: 05/27/2023] Open
Abstract
Due to the continued emergence of resistance and a lack of new and promising antibiotics, bacterial infection has become a major public threat. High-throughput screening (HTS) allows rapid screening of a large collection of molecules for bioactivity testing and holds promise in antibacterial drug discovery. More than 50% of the antibiotics that are currently available on the market are derived from natural products. However, with the easily discoverable antibiotics being found, finding new antibiotics from natural sources has seen limited success. Finding new natural sources for antibacterial activity testing has also proven to be challenging. In addition to exploring new sources of natural products and synthetic biology, omics technology helped to study the biosynthetic machinery of existing natural sources enabling the construction of unnatural synthesizers of bioactive molecules and the identification of molecular targets of antibacterial agents. On the other hand, newer and smarter strategies have been continuously pursued to screen synthetic molecule libraries for new antibiotics and new druggable targets. Biomimetic conditions are explored to mimic the real infection model to better study the ligand-target interaction to enable the designing of more effective antibacterial drugs. This narrative review describes various traditional and contemporaneous approaches of high-throughput screening of natural products and synthetic molecule libraries for antibacterial drug discovery. It further discusses critical factors for HTS assay design, makes a general recommendation, and discusses possible alternatives to traditional HTS of natural products and synthetic molecule libraries for antibacterial drug discovery.
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Affiliation(s)
- Navid J Ayon
- Chemistry of Life Processes Institute, Northwestern University, Evanston, IL 60208, USA
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21
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Eberwine J, Kim J, Anafi RC, Brem S, Bucan M, Fisher SA, Grady MS, Herr AE, Issadore D, Jeong H, Kim H, Lee D, Rubakhin S, Sul JY, Sweedler JV, Wolf JA, Zaret KS, Zou J. Subcellular omics: a new frontier pushing the limits of resolution, complexity and throughput. Nat Methods 2023; 20:331-335. [PMID: 36899160 PMCID: PMC10049458 DOI: 10.1038/s41592-023-01788-0] [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: 03/12/2023]
Abstract
We argue that the study of single-cell subcellular organelle omics is needed to understand and regulate cell function. This requires and is being enabled by new technology development.
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Affiliation(s)
- James Eberwine
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Junhyong Kim
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA.
| | - Ron C Anafi
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Maja Bucan
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Stephen A Fisher
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - M Sean Grady
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amy E Herr
- Department of Bioengineering, University of California at Berkeley, Berkeley, CA, USA
| | - David Issadore
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Hyejoong Jeong
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Chemical and Biomolecular Engineering, , University of Pennsylvania, Philadelphia, PA, USA
| | - HyunBum Kim
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daeyeon Lee
- Department of Chemical and Biomolecular Engineering, , University of Pennsylvania, Philadelphia, PA, USA
| | - Stanislav Rubakhin
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Jai-Yoon Sul
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jonathan V Sweedler
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - John A Wolf
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kenneth S Zaret
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - James Zou
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
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22
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Xu ST, Yang C, Yan XP. Organic Mass Cytometry Discriminating Cycle Stages of Single Cells with Small Molecular Indicators. Anal Chem 2023; 95:2312-2320. [PMID: 36651064 DOI: 10.1021/acs.analchem.2c04165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Cell cycle is a significant factor toward cellular heterogeneity, so cell cycle discrimination is a precise measurement on the top of single-cell analysis. Single-cell analysis based on organic mass spectrometry has received great attention for its unique ability to profile single-cell metabolome, but the influence of cell cycle on cellular metabolome heterogeneity has been overlooked until now due to the lack of a compatible cell cycle discrimination method. Here, we report a robust protocol based on the combination of three small molecular indicators, consisting of two small molecular labels (Hoechst and docetaxel) and one cellular endogenous compound [phosphocholine (34:1)], to discriminate single cells at different cycle stages in real time by organic mass cytometry. More than 6000 HeLa cells were acquired by an improved organic mass cytometry system to build a cell cycle differentiation model. The model successfully discriminated single HeLa cells, SCC7, and Hep G2 cells, at G0/G1, S, and G2/M stages with larger than 85% sensitivity and larger than 89% specificity. Along with cell cycle discrimination, obvious heterogeneity of amino acids, nucleotides, energy metabolic intermediates, and phospholipids was observed among single cells at different cycle stages by this protocol, further demonstrating the necessity of cell cycle discrimination for cellular metabolome heterogeneity research and the potential of more endogenous small molecular compounds for cell cycle discrimination.
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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, Jiangnan University, Wuxi 214122, China.,Institute of Analytical Food Safety, School of Food Science and Technology, 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, Jiangnan University, Wuxi 214122, China.,Institute of Analytical Food Safety, School of Food Science and Technology, 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, Jiangnan University, 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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23
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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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24
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Hu R, Li Y, Yang Y, Liu M. Mass spectrometry-based strategies for single-cell metabolomics. MASS SPECTROMETRY REVIEWS 2023; 42:67-94. [PMID: 34028064 DOI: 10.1002/mas.21704] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 05/05/2021] [Accepted: 05/11/2021] [Indexed: 06/12/2023]
Abstract
Single cell analysis has drawn increasing interest from the research community due to its capability to interrogate cellular heterogeneity, allowing refined tissue classification and facilitating novel biomarker discovery. With the advancement of relevant instruments and techniques, it is now possible to perform multiple omics including genomics, transcriptomics, metabolomics or even proteomics at single cell level. In comparison with other omics studies, single-cell metabolomics (SCM) represents a significant challenge since it involves many types of dynamically changing compounds with a wide range of concentrations. In addition, metabolites cannot be amplified. Although difficult, considerable progress has been made over the past decade in mass spectrometry (MS)-based SCM in terms of processing technologies and biochemical applications. In this review, we will summarize recent progress in the development of promising MS platforms, sample preparation methods and SCM analysis of various cell types (including plant cell, cancer cell, neuron, embryo cell, and yeast cell). Current limitations and future research directions in the field of SCM will also be discussed.
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Affiliation(s)
- Rui Hu
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ying Li
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yunhuang Yang
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Maili Liu
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
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25
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Pan X, Yao H, Zhang S, Zhang X. Recent progress in mass spectrometry for single-cell metabolomics. Curr Opin Chem Biol 2022; 71:102226. [PMID: 36347197 DOI: 10.1016/j.cbpa.2022.102226] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 10/05/2022] [Accepted: 10/09/2022] [Indexed: 11/06/2022]
Abstract
Metabolites are the end products of cellular vital activities and can reflect the state of cellular to a certain extent. Rapid change of metabolites and the low abundance of signature metabolites cause difficulties in single-cell detection, which is a great challenge in single-cell metabolomics analysis. Mass spectrometry (MS) is a powerful tool that uniquely suited to detect intracellular small-molecule metabolites and has shown good application in single-cell metabolite analysis. In this mini-review, we describe three types of emerging technologies for MS-based single-cell metabolic analysis in recent years, including nano-ESI-MS based single-cell metabolomics analysis, high-throughput analysis via flow cytometry, and cellular metabolic imaging analysis. These techniques provide a large amount of single-cell metabolic data, allowing the potential of MS in single-cell metabolic analysis is gradually being explored and is of great importance in disease and life science research.
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Affiliation(s)
- Xingyu Pan
- Department of Chemistry, Tsinghua University, Beijing, China
| | - Huan Yao
- Division of Chemistry and Analytical Science; National Institute of Metrology, Beijing, China
| | - Sichun Zhang
- Department of Chemistry, Tsinghua University, Beijing, China
| | - Xinrong Zhang
- Department of Chemistry, Tsinghua University, Beijing, China.
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26
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Recent advances and typical applications in mass spectrometry-based technologies for single-cell metabolite analysis. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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27
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Tajik M, Baharfar M, Donald WA. Single-cell mass spectrometry. Trends Biotechnol 2022; 40:1374-1392. [PMID: 35562238 DOI: 10.1016/j.tibtech.2022.04.004] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/04/2022] [Accepted: 04/09/2022] [Indexed: 01/21/2023]
Abstract
Owing to recent advances in mass spectrometry (MS), tens to hundreds of proteins, lipids, and small molecules can be measured in single cells. The ability to characterize the molecular heterogeneity of individual cells is necessary to define the full assortment of cell subtypes and identify their function. We review single-cell MS including high-throughput, targeted, mass cytometry-based approaches and antibody-free methods for broad profiling of the proteome and metabolome of single cells. The advantages and disadvantages of different methods are discussed, as well as the challenges and opportunities for further improvements in single-cell MS. These methods is being used in biomedicine in several applications including revealing tumor heterogeneity and high-content drug screening.
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Affiliation(s)
- Mohammad Tajik
- School of Chemistry, University of New South Wales, Sydney, New South Wales, 2052, Australia
| | - Mahroo Baharfar
- School of Chemical Engineering, University of New South Wales, Sydney, New South Wales, 2052, Australia
| | - William A Donald
- School of Chemistry, University of New South Wales, Sydney, New South Wales, 2052, Australia.
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28
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Wang Z, Zhang Y, Tian R, Luo Z, Zhang R, Li X, Abliz Z. Data-Driven Deciphering of Latent Lesions in Heterogeneous Tissue Using Function-Directed t-SNE of Mass Spectrometry Imaging Data. Anal Chem 2022; 94:13927-13935. [PMID: 36173386 DOI: 10.1021/acs.analchem.2c02990] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Mass spectrometry imaging (MSI), which quantifies the underlying chemistry with molecular spatial information in tissue, represents an emerging tool for the functional exploration of pathological progression. Unsupervised machine learning of MSI datasets usually gives an overall interpretation of the metabolic features derived from the abundant ions. However, the features related to the latent lesions are always concealed by the abundant ion features, which hinders precise delineation of the lesions. Herein, we report a data-driven MSI data segmentation approach for recognizing the hidden lesions in the heterogeneous tissue without prior knowledge, which utilizes one-step prediction for feature selection to generate function-specific segmentation maps of the tissue. The performance and robustness of this approach are demonstrated on the MSI datasets of the ischemic rat brain tissues and the human glioma tissue, both possessing different structural complexity and metabolic heterogeneity. Application of the approach to the MSI datasets of the ischemic rat brain tissues reveals the location of the ischemic penumbra, a hidden zone between the ischemic core and the healthy tissue, and instantly discovers the metabolic signatures related to the penumbra. In view of the precise demarcation of latent lesions and the screening of lesion-specific metabolic signatures in tissues, this approach has great potential for in-depth exploration of the metabolic organization of complex tissue.
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Affiliation(s)
- Zixuan Wang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, P. R. China
| | - Yaxin Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, P. R. China
| | - Runtao Tian
- Chemmind Technologies Co., Ltd., Beijing 100085, P. R. China
| | - Zhigang Luo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, P. R. China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, P. R. China
| | - Xin Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, P. R. China.,Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), National Ethnic Affairs Commission, Beijing 100081, P. R. China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, P. R. China.,Center for Imaging and Systems Biology, Minzu University of China, Beijing 100081, P. R. China.,Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), National Ethnic Affairs Commission, Beijing 100081, P. R. China
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29
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Feng Y, Chai H, He W, Liang F, Cheng Z, Wang W. Impedance-Enabled Camera-Free Intrinsic Mechanical Cytometry. SMALL METHODS 2022; 6:e2200325. [PMID: 35595712 DOI: 10.1002/smtd.202200325] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 05/09/2022] [Indexed: 06/15/2023]
Abstract
Mechanical properties of single cells are important label-free biomarkers normally measured by expensive and complex imaging systems. To unlock this limit and allow mechanical properties comparable across different measurement platforms, camera-free intrinsic mechanical cytometry (CFIMC) is proposed for on-the-fly measurement of two major intrinsic mechanical parameters, that is, Young's modulus E and fluidity β, of single cells. CFIMC adopts a framework that couples the impedance electrodes with the constriction channel spatially, so that the impedance signals contain the dynamic deformability information of the cell squeezing through the constriction channel. Deformation of the cell is thus extracted from the impedance signals and used to derive the intrinsic mechanical parameters. With reasonably high throughput (>500 cells min-1 ), CFIMC can successfully reveal the mechanical difference in cancer and normal cells (i.e., human breast cell lines MCF-10A, MCF-7, and MDA-MB-231), living and fixed cells, and pharmacological perturbations of the cytoskeleton. It is further found that 1 µM level concentration of Cytochalasin B may be the threshold for the treated cells to induce a significant cytoskeleton effect reflected by the mechanical parameters. It is envisioned that CFIMC provides an alternative avenue for high-throughput and real-time single-cell intrinsic mechanical analysis.
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Affiliation(s)
- Yongxiang Feng
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, P. R. China
| | - Huichao Chai
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, P. R. China
| | - Weihua He
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, P. R. China
| | - Fei Liang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, P. R. China
| | - Zhen Cheng
- Department of Automation, Tsinghua University, Beijing, 100084, P. R. China
| | - Wenhui Wang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, P. R. China
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30
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Feng D, Li H, Xu T, Zheng F, Hu C, Shi X, Xu G. High-throughput single cell metabolomics and cellular heterogeneity exploration by inertial microfluidics coupled with pulsed electric field-induced electrospray ionization-high resolution mass spectrometry. Anal Chim Acta 2022; 1221:340116. [DOI: 10.1016/j.aca.2022.340116] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 06/20/2022] [Accepted: 06/22/2022] [Indexed: 11/15/2022]
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31
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Lanekoff I, Sharma VV, Marques C. Single-cell metabolomics: where are we and where are we going? Curr Opin Biotechnol 2022; 75:102693. [DOI: 10.1016/j.copbio.2022.102693] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 01/12/2022] [Accepted: 01/20/2022] [Indexed: 12/11/2022]
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32
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Li T, Li S, Shi J, Li X, Liu J, Yang H, Wu W, Zhao L, Zhao Z. Real-time analysis of metabolites in vivo by online extraction electrospray ionization mass spectrometry coupled to microdialysis. Anal Chim Acta 2022; 1205:339760. [DOI: 10.1016/j.aca.2022.339760] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 03/16/2022] [Accepted: 03/22/2022] [Indexed: 01/10/2023]
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33
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Shao Y, Zhou Y, Liu Y, Zhang W, Zhu G, Zhao Y, Zhang Q, Yao H, Zhao H, Guo G, Zhang S, Zhang X, Wang X. Intact living-cell electrolaunching ionization mass spectrometry for single-cell metabolomics. Chem Sci 2022; 13:8065-8073. [PMID: 35919431 PMCID: PMC9278508 DOI: 10.1039/d2sc02569h] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Accepted: 06/17/2022] [Indexed: 11/21/2022] Open
Abstract
A novel living-cell mass spectrometry method allows a whole cell to enter entirely into the MS inlet and ionize with almost no sample dilution and matrix interference, which greatly improves the sensitivity of single-cell metabolite detection.
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Affiliation(s)
- Yunlong Shao
- Department of Chemistry and Biology, Center of Excellence for Environmental Safety and Biological Effects, Beijing Key Laboratory for Green Catalysis and Separation, Beijing University of Technology, Beijing 100124, P. R. China
| | - Yingyan Zhou
- Department of Chemistry and Biology, Center of Excellence for Environmental Safety and Biological Effects, Beijing Key Laboratory for Green Catalysis and Separation, Beijing University of Technology, Beijing 100124, P. R. China
| | - Yuanxing Liu
- Department of Chemistry and Biology, Center of Excellence for Environmental Safety and Biological Effects, Beijing Key Laboratory for Green Catalysis and Separation, Beijing University of Technology, Beijing 100124, P. R. China
| | - Wenmei Zhang
- Department of Chemistry and Biology, Center of Excellence for Environmental Safety and Biological Effects, Beijing Key Laboratory for Green Catalysis and Separation, Beijing University of Technology, Beijing 100124, P. R. China
| | - Guizhen Zhu
- Department of Chemistry and Biology, Center of Excellence for Environmental Safety and Biological Effects, Beijing Key Laboratory for Green Catalysis and Separation, Beijing University of Technology, Beijing 100124, P. R. China
| | - Yaoyao Zhao
- Department of Chemistry and Biology, Center of Excellence for Environmental Safety and Biological Effects, Beijing Key Laboratory for Green Catalysis and Separation, Beijing University of Technology, Beijing 100124, P. R. China
| | - Qi Zhang
- Department of Chemistry and Biology, Center of Excellence for Environmental Safety and Biological Effects, Beijing Key Laboratory for Green Catalysis and Separation, Beijing University of Technology, Beijing 100124, P. R. China
| | - Huan Yao
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Hansen Zhao
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Guangsheng Guo
- Department of Chemistry and Biology, Center of Excellence for Environmental Safety and Biological Effects, Beijing Key Laboratory for Green Catalysis and Separation, Beijing University of Technology, Beijing 100124, P. R. China
- Minzu University of China, Beijing 100081, P. R. China
| | - Sichun Zhang
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Xinrong Zhang
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Xiayan Wang
- Department of Chemistry and Biology, Center of Excellence for Environmental Safety and Biological Effects, Beijing Key Laboratory for Green Catalysis and Separation, Beijing University of Technology, Beijing 100124, P. R. China
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34
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Shen Z, Zhao H, Yao H, Pan X, Yang J, Zhang S, Han G, Zhang X. Dynamic metabolic change of cancer cells induced by natural killer cells at single-cell level studied by label-free mass cytometry. Chem Sci 2022; 13:1641-1647. [PMID: 35282636 PMCID: PMC8827047 DOI: 10.1039/d1sc06366a] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 12/31/2021] [Indexed: 01/10/2023] Open
Abstract
Natural killer cells (NK cells) are important immune cells which have attracted increasing attention in cancer immunotherapy. Due to the heterogeneity of cells, individual cancer cells show different resistance to NK cytotoxicity, which has been revealed by flow cytometry. Here we used label-free mass cytometry (CyESI-MS) as a new tool to analyze the metabolites in Human Hepatocellular Carcinoma (HepG2) cells at the single-cell level after the interaction with different numbers of NK92 MI cells. A large amount of chemical information from individual HepG2 cells was obtained showing the process of cell apoptosis induced by NK cells. Nineteen metabolites which consecutively change during cell apoptosis were revealed by calculating their average relative intensity. Four metabolic pathways were impacted during cell apoptosis which hit 4 metabolites including glutathione (GSH), creatine, glutamic acid and taurine. We found that the HepG2 cells could be divided into two phenotypes after co-culturing with NK cells according to the bimodal distribution of concentration of these 4 metabolites. The correlation between metabolites and different apoptotic pathways in the early apoptosis cell group was established by the 4 metabolites at the single-cell level. This is a new idea of using single-cell specific metabolites to reveal the metabolic heterogeneity in cell apoptosis which would be a powerful means for evaluating the cytotoxicity of NK cells. Label-free mass cytometry is utilized to study the dynamic metabolic change during apoptosis in HepG2 cells induced by NK92 MI cells at the single-cell level. The metabolic heterogeneity of individual HepG2 cells during apoptosis was revealed.![]()
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Affiliation(s)
- Zizheng Shen
- Department of Chemistry, Tsinghua University Beijing 100084 China
| | - Hansen Zhao
- Department of Chemistry, Tsinghua University Beijing 100084 China
| | - Huan Yao
- Department of Chemistry, Tsinghua University Beijing 100084 China
| | - Xingyu Pan
- Department of Chemistry, Tsinghua University Beijing 100084 China
| | - Jinlei Yang
- Department of Chemistry, Tsinghua University Beijing 100084 China
| | - Sichun Zhang
- Department of Chemistry, Tsinghua University Beijing 100084 China
| | - Guojun Han
- Institute of Medical Technology, Peking University Health Science Center Beijing 100191 China
- Peking University School and Hospital of Stomatology Beijing 100081 P. R. China
- Department of Biomedical Engineering, Peking University Health Science Center Beijing 100191 P. R. China
| | - Xinrong Zhang
- Department of Chemistry, Tsinghua University Beijing 100084 China
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35
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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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36
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Toward modeling metabolic state from single-cell transcriptomics. Mol Metab 2021; 57:101396. [PMID: 34785394 PMCID: PMC8829761 DOI: 10.1016/j.molmet.2021.101396] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 10/21/2021] [Accepted: 11/09/2021] [Indexed: 12/31/2022] Open
Abstract
Background Single-cell metabolic studies bring new insights into cellular function, which can often not be captured on other omics layers. Metabolic information has wide applicability, such as for the study of cellular heterogeneity or for the understanding of drug mechanisms and biomarker development. However, metabolic measurements on single-cell level are limited by insufficient scalability and sensitivity, as well as resource intensiveness, and are currently not possible in parallel with measuring transcript state, commonly used to identify cell types. Nevertheless, because omics layers are strongly intertwined, it is possible to make metabolic predictions based on measured data of more easily measurable omics layers together with prior metabolic network knowledge. Scope of Review We summarize the current state of single-cell metabolic measurement and modeling approaches, motivating the use of computational techniques. We review three main classes of computational methods used for prediction of single-cell metabolism: pathway-level analysis, constraint-based modeling, and kinetic modeling. We describe the unique challenges arising when transitioning from bulk to single-cell modeling. Finally, we propose potential model extensions and computational methods that could be leveraged to achieve these goals. Major Conclusions Single-cell metabolic modeling is a rising field that provides a new perspective for understanding cellular functions. The presented modeling approaches vary in terms of input requirements and assumptions, scalability, modeled metabolic layers, and newly gained insights. We believe that the use of prior metabolic knowledge will lead to more robust predictions and will pave the way for mechanistic and interpretable machine-learning models. Single-cell RNA sequencing and prior metabolic knowledge enable metabolic predictions. When compared to bulk, single-cell modeling is linked to unique insights and challenges. Computational modelling approaches differ in applicability and newly provided insights. The use of prior metabolic knowledge paves the way for mechanistic machine-learning.
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Liu Q, Ge W, Wang T, Lan J, Martínez‐Jarquín S, Wolfrum C, Stoffel M, Zenobi R. High‐Throughput Single‐Cell Mass Spectrometry Reveals Abnormal Lipid Metabolism in Pancreatic Ductal Adenocarcinoma. Angew Chem Int Ed Engl 2021. [DOI: 10.1002/ange.202107223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Qinlei Liu
- Department of Chemistry and Applied Biosciences ETH Zurich Vladimir-Prelog-Weg 3 8093 Zurich Switzerland
| | - Wenjie Ge
- Department of Biology ETH Zurich Otto-Stern-Weg 7 8093 Zurich Switzerland
| | - Tongtong Wang
- Department of Health Sciences and Technology ETH Zurich Schorenstrasse 16 8603 Schwerzenbach Switzerland
| | - Jiayi Lan
- Department of Chemistry and Applied Biosciences ETH Zurich Vladimir-Prelog-Weg 3 8093 Zurich Switzerland
| | - Sandra Martínez‐Jarquín
- Department of Chemistry and Applied Biosciences ETH Zurich Vladimir-Prelog-Weg 3 8093 Zurich Switzerland
| | - Christian Wolfrum
- Department of Health Sciences and Technology ETH Zurich Schorenstrasse 16 8603 Schwerzenbach Switzerland
| | - Markus Stoffel
- Department of Biology ETH Zurich Otto-Stern-Weg 7 8093 Zurich Switzerland
| | - Renato Zenobi
- Department of Chemistry and Applied Biosciences ETH Zurich Vladimir-Prelog-Weg 3 8093 Zurich Switzerland
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38
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Liu Q, Ge W, Wang T, Lan J, Martínez‐Jarquín S, Wolfrum C, Stoffel M, Zenobi R. High-Throughput Single-Cell Mass Spectrometry Reveals Abnormal Lipid Metabolism in Pancreatic Ductal Adenocarcinoma. Angew Chem Int Ed Engl 2021; 60:24534-24542. [PMID: 34505339 PMCID: PMC8597026 DOI: 10.1002/anie.202107223] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Revised: 08/17/2021] [Indexed: 01/02/2023]
Abstract
Even populations of clonal cells are heterogeneous, which requires high-throughput analysis methods with single-cell sensitivity. Here, we propose a rapid, label-free single-cell analytical method based on active capillary dielectric barrier discharge ionization mass spectrometry, which can analyze multiple metabolites in single cells at a rate of 38 cells/minute. Multiple cell types (HEK-293T, PANC-1, CFPAC-1, H6c7, HeLa and iBAs) were discriminated successfully. We found evidence for abnormal lipid metabolism in pancreatic cancer cells. We also analyzed gene expression in a cancer genome atlas dataset and found that the mRNA level of a critical enzyme of lipid synthesis (ATP citrate lyase, ACLY) was upregulated in human pancreatic ductal adenocarcinoma (PDAC). Moreover, both an ACLY chemical inhibitor and a siRNA approach targeting ACLY could suppress the viability of PDAC cells. A significant reduction in lipid content in treated cells indicates that ACLY could be a potential target for treating pancreatic cancer.
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Affiliation(s)
- Qinlei Liu
- Department of Chemistry and Applied BiosciencesETH ZurichVladimir-Prelog-Weg 38093ZurichSwitzerland
| | - Wenjie Ge
- Department of BiologyETH ZurichOtto-Stern-Weg 78093ZurichSwitzerland
| | - Tongtong Wang
- Department of Health Sciences and TechnologyETH ZurichSchorenstrasse 168603SchwerzenbachSwitzerland
| | - Jiayi Lan
- Department of Chemistry and Applied BiosciencesETH ZurichVladimir-Prelog-Weg 38093ZurichSwitzerland
| | - Sandra Martínez‐Jarquín
- Department of Chemistry and Applied BiosciencesETH ZurichVladimir-Prelog-Weg 38093ZurichSwitzerland
| | - Christian Wolfrum
- Department of Health Sciences and TechnologyETH ZurichSchorenstrasse 168603SchwerzenbachSwitzerland
| | - Markus Stoffel
- Department of BiologyETH ZurichOtto-Stern-Weg 78093ZurichSwitzerland
| | - Renato Zenobi
- Department of Chemistry and Applied BiosciencesETH ZurichVladimir-Prelog-Weg 38093ZurichSwitzerland
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39
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Li Y, Li H, Xie Y, Chen S, Qin R, Dong H, Yu Y, Wang J, Qian X, Qin W. An Integrated Strategy for Mass Spectrometry-Based Multiomics Analysis of Single Cells. Anal Chem 2021; 93:14059-14067. [PMID: 34643370 DOI: 10.1021/acs.analchem.0c05209] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Single-cell-based genomics and transcriptomics analysis have revealed substantial cellular heterogeneity among seemingly identical cells. Knowledge of the cellular heterogeneity at multiomics levels is vital for a better understanding of tumor metastasis and drug resistance, stem cell differentiation, and embryonic development. However, unlike genomics and transcriptomics studies, single-cell characterization of metabolites, proteins, and post-translational modifications at the omics level remains challenging due to the lack of amplification methods and the wide diversity of these biomolecules. Therefore, new tools that are capable of investigating these unamplifiable "omes" from the same single cells are in high demand. In this work, a microwell chip was prepared and the internal surface was modified for hydrophilic interaction liquid chromatography-based tandem extraction of metabolites and proteins and subsequent protein digestion. Next, direct electrospray ionization mass spectrometry was adopted for single-cell metabolome identification, and a data-independent acquisition-mass spectrometry approach was established for simultaneous proteome profiling and phosphoproteome analysis without phosphopeptide enrichment. This integrated strategy resulted in 132 putatively annotated compounds, more than 1200 proteins, and the first large-scale phosphorylation data set from single-cell analysis. Application of this strategy in chemical perturbation studies provides a multiomics view of cellular changes, demonstrating its capability for more comprehensive investigation of cellular heterogeneity.
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Affiliation(s)
- Yuanyuan Li
- Research Center for Analytical Sciences, College of Sciences, Northeastern University, Shenyang 110819, P. R. China
| | - Hang Li
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Yuping Xie
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Shuo Chen
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Ritian Qin
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Hangyan Dong
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Yongliang Yu
- Research Center for Analytical Sciences, College of Sciences, Northeastern University, Shenyang 110819, P. R. China
| | - Jianhua Wang
- Research Center for Analytical Sciences, College of Sciences, Northeastern University, Shenyang 110819, P. R. China
| | - Xiaohong Qian
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Weijie Qin
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China.,College of Basic Medicine, Anhui Medical University, Hefei 230032, P. R. China
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40
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Zhu G, Shao Y, Liu Y, Pei T, Li L, Zhang D, Guo G, Wang X. Single-cell metabolite analysis by electrospray ionization mass spectrometry. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116351] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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41
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Xu S, Yang C, Yan X, Liu H. Towards high throughput and high information coverage: advanced single-cell mass spectrometric techniques. Anal Bioanal Chem 2021; 414:219-233. [PMID: 34435209 DOI: 10.1007/s00216-021-03624-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 08/13/2021] [Accepted: 08/17/2021] [Indexed: 12/23/2022]
Abstract
Mass spectrometry (MS) is attractive for single-cell analysis because of its high sensitivity, rich information, and large dynamic ranges, especially for the single-cell metabolome and proteome analysis. Efforts have been made to deal with the throughput and information coverage problems in typical manual single-cell MS techniques. In this review, advanced techniques to improve the automation and throughput for single-cell sampling and single-cell metabolome and proteome MS detection have been discussed. Furthermore, representative MS-based strategies that can increase the in-depth cellular information coverage and achieve the more comprehensive single-cell multiomics information during high throughput detection have been highlighted, providing an ongoing perspective of the MS performance for the single-cell research.
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Affiliation(s)
- Shuting Xu
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China.,Institute of Analytical Food Safety, School of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China
| | - Cheng Yang
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China.,Institute of Analytical Food Safety, School of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China
| | - Xiuping Yan
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China. .,Institute of Analytical Food Safety, School of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China.
| | - Huwei Liu
- Institute of Analytical Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China.
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42
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Zhang L, Xu T, Zhang J, Wong SCC, Ritchie M, Hou HW, Wang Y. Single Cell Metabolite Detection Using Inertial Microfluidics-Assisted Ion Mobility Mass Spectrometry. Anal Chem 2021; 93:10462-10468. [PMID: 34289696 DOI: 10.1021/acs.analchem.1c00106] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Single-cell metabolite measurement remains highly challenging due to difficulties related to single cell isolation, metabolite detection, and identification of low levels of metabolites. Here, as a first step of the technological development, we propose a novel strategy integrating spiral inertial microfluidics and ion mobility mass spectrometry (IM-MS) for single-cell metabolite detection and identification. Cells in methanol suspension are inertially focused into a single stream in the spiral microchannel. This stream of separated cells is delivered to the nanoelectrospray needle to be lysed and ionized and subsequently analyzed in real time by IM-MS. This analytical system enables six to eight single-cell metabolic fingerprints to be collected per minute, including gas-phase collisional cross section (CCS) measurements as an additional molecular descriptor, giving increased confidence in metabolite identification. As a proof of concept, the metabolic profiles of three types of cancer cells (U2OS, HepG2, and HepG2.215) were successfully screened, and 19 distinct lipids species were identified with CCS value filtering. Furthermore, principal component analysis (PCA) showed differentiation of the three cancer cell lines, mainly due to cellular surface phospholipids. Taken together, our technology platform offers a simple and efficient method for single-cell lipid profiling, with additional ion mobility separation of lipids significantly improving the confidence toward identification of metabolites.
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Affiliation(s)
- Leicheng Zhang
- Singapore Phenome Center, Lee Kong Chian School of Medicine, Nanyang Technological University, 639798 Singapore
| | - Tengfei Xu
- School of Civil and Environmental Engineering, Nanyang Technological University, 639798 Singapore
| | - Jingtao Zhang
- Singapore Phenome Center, Lee Kong Chian School of Medicine, Nanyang Technological University, 639798 Singapore
| | | | - Mark Ritchie
- Waters Pacific Pte Ltd, Science Park 2, 117528 Singapore
| | - Han Wei Hou
- Singapore Phenome Center, Lee Kong Chian School of Medicine, Nanyang Technological University, 639798 Singapore.,School of Mechanical & Aerospace Engineering, Nanyang Technological University, 639798 Singapore
| | - Yulan Wang
- Singapore Phenome Center, Lee Kong Chian School of Medicine, Nanyang Technological University, 639798 Singapore
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43
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Yao H, Zhao H, Pan X, Zhao X, Feng J, Yang C, Zhang S, Zhang X. Discriminating Leukemia Cellular Heterogeneity and Screening Metabolite Biomarker Candidates using Label-Free Mass Cytometry. Anal Chem 2021; 93:10282-10291. [PMID: 34259005 DOI: 10.1021/acs.analchem.1c01746] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Discriminating various leukocyte subsets with specific functions is critical due to their important roles in the development of many diseases. Here, we proposed a general strategy to unravel leukocytes heterogeneity and screen differentiated metabolites as biomarker candidates for leukocyte subtypes using the label-free mass cytometry (CyESI-MS) combined with a homemade data processing workflow. Taking leukemia cells as an example, metabolic fingerprints of single leukemia cells were obtained from 472 HL-60, 416 THP-1, 313 U937, 356 Jurkat, and 366 Ramos cells, with throughput up to 40 cells/min. Five leukemia subtypes were clearly distinguished by unsupervised learning t-SNE analysis of the single-cell metabolic fingerprints. Cell discrimination in the mixed leukemia cell samples was also realized by supervised learning of the single-cell metabolic fingerprints with high recovery and good repetition (98.31 ± 0.24%, -102.35 ± 4.82%). Statistical analysis and metabolite assignment were carried out to screen characteristic metabolites for discrimination and 36 metabolites with significant differences were annotated. Then, differentiated metabolites for pairwise discrimination of five leukemia subtypes were further selected as biomarker candidates. Furthermore, discriminating cultured leukemia cells from human normal leukocytes, separated from fresh human peripheral blood, was performed based on single-cell metabolic fingerprints as well as the proposed biomarker candidates, unveiling the potential of this strategy in clinical research. This work makes efforts to realize high-throughput single-leukocyte metabolic analysis and metabolite-based discrimination of leukocytes. It is expected to be a powerful means for the clinical molecular diagnosis of hematological diseases.
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Affiliation(s)
- Huan Yao
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Hansen Zhao
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Xingyu Pan
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Xu Zhao
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Jiaxin Feng
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Chengdui Yang
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Sichun Zhang
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
| | - Xinrong Zhang
- Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China
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44
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Metabolomic profiling of single enlarged lysosomes. Nat Methods 2021; 18:788-798. [PMID: 34127857 DOI: 10.1038/s41592-021-01182-8] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 05/10/2021] [Indexed: 02/05/2023]
Abstract
Lysosomes are critical for cellular metabolism and are heterogeneously involved in various cellular processes. The ability to measure lysosomal metabolic heterogeneity is essential for understanding their physiological roles. We therefore built a single-lysosome mass spectrometry (SLMS) platform integrating lysosomal patch-clamp recording and induced nano-electrospray ionization (nanoESI)/mass spectrometry (MS) that enables concurrent metabolic and electrophysiological profiling of individual enlarged lysosomes. The accuracy and reliability of this technique were validated by supporting previous findings, such as the transportability of lysosomal cationic amino acids transporters such as PQLC2 and the lysosomal trapping of lysosomotropic, hydrophobic weak base drugs such as lidocaine. We derived metabolites from single lysosomes in various cell types and classified lysosomes into five major subpopulations based on their chemical and biological divergence. Senescence and carcinoma altered metabolic profiles of lysosomes in a type-specific manner. Thus, SLMS can open more avenues for investigating heterogeneous lysosomal metabolic changes during physiological and pathological processes.
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45
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Chen A, Yan M, Feng J, Bi L, Chen L, Hu S, Hong H, Shi L, Li G, Jin B, Zhang X, Wen L. Single Cell Mass Spectrometry with a Robotic Micromanipulation System for Cell Metabolite Analysis. IEEE Trans Biomed Eng 2021; 69:325-333. [PMID: 34185636 DOI: 10.1109/tbme.2021.3093097] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
ObjectiveThe increasing demand for unraveling cellular heterogeneity has boosted single cell metabolomics studies. However, current analytical methods are usually labor-intensive and hampered by lack of accuracy and efficiency. METHODS we developed a first-ever automated single cell mass spectrometry system (named SCMS) that facilitated the metabolic profiling of single cells. In particular, extremely small droplets of sub nano-liter were generated to extract the single cells, and the underlying mechanism was verified theoretically and experimentally. This was crucial to minimize the dilution of the trace cellular contents and enhance the analytical sensitivity. Based on the precise 3D positioning of the pipette tip, we established a visual servoing robotic micromanipulation platform on which single cells were sequentially extracted, aspirated, and ionized, followed by the mass spectrometry analyses. RESULTS With the SCMS system, inter-operator variability was eliminated and working efficiency was improved. The performance of the SCMS system was validated by the experiments on bladder cancer cells. MS and MS2 analyses of single cells enable us to identify several cellular metabolites and the underlying inter-cell heterogeneity. CONCLUSION In contrast to traditional methods, the SCMS system functions without human intervention and realizes a robust single cell metabolic analysis. SIGNIFICANCE the SCMS system upgrades the way how single cell metabolites were analyzed, and has the potential to be a powerful tool for single cell metabolomics studies.
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46
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Li Z, Cheng S, Lin Q, Cao W, Yang J, Zhang M, Shen A, Zhang W, Xia Y, Ma X, Ouyang Z. Single-cell lipidomics with high structural specificity by mass spectrometry. Nat Commun 2021; 12:2869. [PMID: 34001877 PMCID: PMC8129106 DOI: 10.1038/s41467-021-23161-5] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 04/15/2021] [Indexed: 12/12/2022] Open
Abstract
Single-cell analysis is critical to revealing cell-to-cell heterogeneity that would otherwise be lost in ensemble analysis. Detailed lipidome characterization for single cells is still far from mature, especially when considering the highly complex structural diversity of lipids and the limited sample amounts available from a single cell. We report the development of a general strategy enabling single-cell lipidomic analysis with high structural specificity. Cell fixation is applied to retain lipids in the cell during batch treatments prior to single-cell analysis. In addition to tandem mass spectrometry analysis revealing the class and fatty acyl-chain for lipids, batch photochemical derivatization and single-cell droplet treatment are performed to identify the C=C locations and sn-positions of lipids, respectively. Electro-migration combined with droplet-assisted electrospray ionization enables single-cell mass spectrometry analysis with easy operation but high efficiency in sample usage. Four subtypes of human breast cancer cells are correctly classified through quantitative analysis of lipid C=C location or sn-position isomers in ~160 cells. Most importantly, the single-cell deep lipidomics strategy successfully discriminates gefitinib-resistant cells from a population of wild-type human lung cancer cells (HCC827), highlighting its unique capability to promote precision medicine.
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Affiliation(s)
- Zishuai Li
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
| | - Simin Cheng
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
| | - Qiaohong Lin
- MOE Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Department of Chemistry, Tsinghua University, Beijing, China
| | - Wenbo Cao
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
| | - Jing Yang
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
| | - Minmin Zhang
- Division of Anti-tumor Pharmacology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Aijun Shen
- Division of Anti-tumor Pharmacology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Wenpeng Zhang
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China
| | - Yu Xia
- MOE Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Department of Chemistry, Tsinghua University, Beijing, China
| | - Xiaoxiao Ma
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China.
| | - Zheng Ouyang
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China.
- Department of Chemistry, Purdue University, West Lafayette, IN, USA.
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47
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Gao T, Gao X, Xu C, Wang M, Chen M, Wang J, Ma F, Yu P, Mao L. Label-Free Resistance Cytometry at the Orifice of a Nanopipette. Anal Chem 2021; 93:2942-2949. [PMID: 33502179 DOI: 10.1021/acs.analchem.0c04585] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Development of new principles and techniques at the single-cell level is significantly important since cells as basic units of living organisms always bear large heterogeneity. Herein, we demonstrate a new electrochemical principle for single-cell analysis based on an ion current blockage at the orifice of a nanopipette, defined as resistance cytometry. The amplitude and the frequency of ion current transients show strong dependence on the size and the concentration of cells, which could be used for in situ cell sizing and counting. This technique shows good ability to detect the size change of RBCs under stimulations of different pH and osmotic pressure values. More importantly, the as-presented resistance cytometry can distinguish lymphoma blood cells from normal blood cells for patient blood samples. The as-presented resistance cytometry is label-free, non-invasive, and non-destructive, which not only opens new opportunities for single-cell analysis but also provides a new platform for cell-related medical diagnostic technologies.
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Affiliation(s)
- Tienan Gao
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Box 332, Shenyang 110819, China.,Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Xiangyi Gao
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Cong Xu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.,School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Menglin Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.,Department of Otolaryngology Head and Neck Surgery, Peking University Third Hospital, Beijing 100191, China
| | - Mingli Chen
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Box 332, Shenyang 110819, China
| | - Jianhua Wang
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Box 332, Shenyang 110819, China
| | - Furong Ma
- Department of Otolaryngology Head and Neck Surgery, Peking University Third Hospital, Beijing 100191, China
| | - Ping Yu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.,School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lanqun Mao
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.,College of Chemistry, Beijing Normal University, Beijing 100875, China.,School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
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Liu R, Yang Z. Single cell metabolomics using mass spectrometry: Techniques and data analysis. Anal Chim Acta 2021; 1143:124-134. [PMID: 33384110 PMCID: PMC7775990 DOI: 10.1016/j.aca.2020.11.020] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 11/10/2020] [Accepted: 11/17/2020] [Indexed: 02/06/2023]
Abstract
Mass spectrometry (MS) based techniques are gaining popularity for metabolomics research due to their high sensitivity, wide detection range, and capability of molecular identification. Utilizing such powerful technique to explore the cellular metabolism at the single cell level not only appreciates the subtle cell-to-cell difference (i.e., cell heterogeneity), but also gains biological merits corresponding to individual cells or small cell subpopulations. In this review article, we first briefly summarize recent advances in single cell MS experimental techniques, and then emphasize on the single cell metabolomics data analysis approaches. Through implementation of statistical analysis and more advanced data analysis methods, single cell metabolomics is expected to find more potential applications in the translational and clinical fields in the future.
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Affiliation(s)
- Renmeng Liu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA; Alliance Pharma. Inc., Malvern, PA, 19355, USA
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA.
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Affiliation(s)
- Keke Hu
- Department of Chemistry and Molecular Biology, University of Gothenburg, Kemivägen 10, 41296 Gothenburg, Sweden
| | - Tho D. K. Nguyen
- Department of Chemistry and Molecular Biology, University of Gothenburg, Kemivägen 10, 41296 Gothenburg, Sweden
| | - Stefania Rabasco
- Department of Chemistry and Molecular Biology, University of Gothenburg, Kemivägen 10, 41296 Gothenburg, Sweden
| | - Pieter E. Oomen
- Department of Chemistry and Molecular Biology, University of Gothenburg, Kemivägen 10, 41296 Gothenburg, Sweden
- ParaMedir B.V., 1e Energieweg 13, 9301 LK Roden, The Netherlands
| | - Andrew G. Ewing
- Department of Chemistry and Molecular Biology, University of Gothenburg, Kemivägen 10, 41296 Gothenburg, Sweden
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50
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Xu S, Liu M, Bai Y, Liu H. Multi-Dimensional Organic Mass Cytometry: Simultaneous Analysis of Proteins and Metabolites on Single Cells. Angew Chem Int Ed Engl 2020; 60:1806-1812. [PMID: 33085796 DOI: 10.1002/anie.202009682] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Indexed: 12/11/2022]
Abstract
Mass cytometry is attracting significant attention for enabling spatiotemporal high-throughput single-cell analysis. As the first demonstration of the simultaneous detection of single-cell proteins and untargeted metabolites, a multi-dimensional organic mass-cytometry system was established by a simple microfluidic chip connected to a nanoelectrospray mass spectrometer, providing useful heterogeneous information about the cells. A series of mass probes with online-dissociated mass tags were developed, ensuring the semi-quantification of cell-surface proteins and the compatibility of endogenous metabolite detection at the single-cell level. Six cell surface antigens and ≈100 metabolites from three ovarian-cancer cell types and two breast-cancer cell types were successfully monitored and contributed to highly sensitive and specific cell typing. Doxorubicin-resistant cancer-cell analysis confirmed the applications in distinguishing rare cell phenotypes. The proposed system is simple, extensible, and promising for cell typing, drug-resistance analysis of tumor cells, and clinical diagnosis and therapy at the single-cell level.
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Affiliation(s)
- Shuting Xu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, P. R. China
| | - Mingxia Liu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, P. R. China
| | - Yu Bai
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, P. R. China
| | - Huwei Liu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, P. R. China
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