1
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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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2
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Lan Y, Chen X, Yang Z. Quantification of Nitric Oxide in Single Cells Using the Single-Probe Mass Spectrometry Technique. Anal Chem 2023; 95:18871-18879. [PMID: 38092461 DOI: 10.1021/acs.analchem.3c04393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Nitric oxide (NO) is a small molecule that plays important roles in biological systems and human diseases. The abundance of intracellular NO is tightly related to numerous biological processes. Due to cell heterogeneity, the intracellular NO amounts significantly vary from cell to cell, and therefore, any meaningful studies need to be conducted at the single-cell level. However, measuring NO in single cells is very challenging, primarily due to the extremely small size of single cells and reactive nature of NO. In the current studies, the quantitative reaction between NO and amlodipine, a compound containing the Hantzsch ester group, was performed in live cells. The product dehydro amlodipine was then detected by the Single-probe single-cell mass spectrometry technique to quantify NO in single cells. The experimental results indicated heterogeneous distributions of intracellular NO amounts in single cells with the existence of subpopulations.
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Affiliation(s)
- Yunpeng Lan
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Xingxiu Chen
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
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3
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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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4
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Lu H, Zhang H, Li L. Chemical tagging mass spectrometry: an approach for single-cell omics. Anal Bioanal Chem 2023; 415:6901-6913. [PMID: 37466681 PMCID: PMC10729908 DOI: 10.1007/s00216-023-04850-0] [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: 04/10/2023] [Revised: 07/04/2023] [Accepted: 07/06/2023] [Indexed: 07/20/2023]
Abstract
Single-cell (SC) analysis offers new insights into the study of fundamental biological phenomena and cellular heterogeneity. The superior sensitivity, high throughput, and rich chemical information provided by mass spectrometry (MS) allow MS to emerge as a leading technology for molecular profiling of SC omics, including the SC metabolome, lipidome, and proteome. However, issues such as ionization suppression, low concentration, and huge span of dynamic concentrations of SC components lead to poor MS response for certain types of molecules. It is noted that chemical tagging/derivatization has been adopted in SCMS analysis, and this strategy has been proven an effective solution to circumvent these issues in SCMS analysis. Herein, we review the basic principle and general strategies of chemical tagging/derivatization in SCMS analysis, along with recent applications of chemical derivatization to single-cell metabolomics and multiplexed proteomics, as well as SCMS imaging. Furthermore, the challenges and opportunities for the improvement of chemical derivatization strategies in SCMS analysis are discussed.
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Affiliation(s)
- Haiyan Lu
- School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Hua Zhang
- School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Lingjun Li
- School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA.
- Lachman Institute for Pharmaceutical Development, School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA.
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5
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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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6
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Hancock SE, Ding E, Johansson Beves E, Mitchell T, Turner N. FACS-assisted single-cell lipidome analysis of phosphatidylcholines and sphingomyelins in cells of different lineages. J Lipid Res 2023; 64:100341. [PMID: 36740022 PMCID: PMC10027561 DOI: 10.1016/j.jlr.2023.100341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 01/16/2023] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
Recent advances in single-cell genomics and transcriptomics technologies have transformed our understanding of cellular heterogeneity in growth, development, ageing, and disease; however, methods for single-cell lipidomics have comparatively lagged behind in development. We have developed a method for the detection and quantification of a wide range of phosphatidylcholine and sphingomyelin species from single cells that combines fluorescence-assisted cell sorting with automated chip-based nanoESI and shotgun lipidomics. We show herein that our method is capable of quantifying more than 50 different phosphatidylcholine and sphingomyelin species from single cells and can easily distinguish between cells of different lineages or cells treated with exogenous fatty acids. Moreover, our method can detect more subtle differences in the lipidome between cell lines of the same cancer type. Our approach can be run in parallel with other single-cell technologies to deliver near-complete, high-throughput multi-omics data on cells with a similar phenotype and has the capacity to significantly advance our current knowledge on cellular heterogeneity.
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Affiliation(s)
- Sarah E Hancock
- Department of Pharmacology, School of Biomedical Sciences, UNSW Sydney, Australia; Cellular Bioenergetics Laboratory, Victor Chang Cardiac Research Institute, Sydney, NSW, Australia.
| | - Eileen Ding
- Department of Pharmacology, School of Biomedical Sciences, UNSW Sydney, Australia
| | | | - Todd Mitchell
- School of Medicine, University of Wollongong, Wollongong Australia; Molecular Horizons, University of Wollongong, Wollongong Australia
| | - Nigel Turner
- Department of Pharmacology, School of Biomedical Sciences, UNSW Sydney, Australia; Cellular Bioenergetics Laboratory, Victor Chang Cardiac Research Institute, Sydney, NSW, Australia.
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7
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Václavek T, Foret F. Microfluidic device integrating single-cell extraction and electrical lysis for mass spectrometry detection of intracellular compounds. Electrophoresis 2023; 44:313-322. [PMID: 35315940 DOI: 10.1002/elps.202100379] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/26/2022] [Accepted: 01/28/2022] [Indexed: 02/01/2023]
Abstract
Analysis of cellular composition and metabolism at a single-cell resolution allows gaining more information about complex relationships of cells within tissues or whole living organisms by resolving the variance stemming from the cellular heterogeneity. Mass spectrometry (MS) is a perfect analytical tool satisfying the demanding requirements of detecting and identifying compounds present in such ultralow-volume samples of high chemical complexity. However, the method of sampling and sample ionization is crucial in obtaining relevant information. In this work, we present a microfluidic sampling platform that integrates single-cell extraction from MS-incompatible media with electrical cell lysis and nanoESI-MS analysis of human erythrocytes. Hemoglobin alpha and beta chains (300 amol/cell) were successfully identified in mass spectra of single-erythrocyte lysates.
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Affiliation(s)
- Tomáš Václavek
- Department of Bioanalytical Instrumentation, Institute of Analytical Chemistry of the CAS, Brno, Czech Republic.,Department of Biochemistry, Masaryk University, Brno, Czech Republic
| | - František Foret
- Department of Bioanalytical Instrumentation, Institute of Analytical Chemistry of the CAS, Brno, Czech Republic
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8
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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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9
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Toth T, Bauer D, Sukosd F, Horvath P. Fisheye transformation enhances deep-learning-based single-cell phenotyping by including cellular microenvironment. CELL REPORTS METHODS 2022; 2:100339. [PMID: 36590690 PMCID: PMC9795324 DOI: 10.1016/j.crmeth.2022.100339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 08/22/2022] [Accepted: 10/21/2022] [Indexed: 11/23/2022]
Abstract
Incorporating information about the surroundings can have a significant impact on successfully determining the class of an object. This is of particular interest when determining the phenotypes of cells, for example, in the context of high-throughput screens. We hypothesized that an ideal approach would consider the fully featured view of the cell of interest, include its neighboring microenvironment, and give lesser weight to cells that are far from the cell of interest. To satisfy these criteria, we present an approach with a transformation similar to those characteristic of fisheye cameras. Using this transformation with proper settings, we could significantly increase the accuracy of single-cell phenotyping, both in the case of cell culture and tissue-based microscopy images, and we present improved results on a dataset containing images of wild animals.
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Affiliation(s)
- Timea Toth
- Synthetic and Systems Biology Unit, Biological Research Centre, Eötvös Loránd Research Network, Szeged, Hungary
- Doctoral School of Biology, University of Szeged, Szeged, Hungary
| | - David Bauer
- Synthetic and Systems Biology Unit, Biological Research Centre, Eötvös Loránd Research Network, Szeged, Hungary
| | - Farkas Sukosd
- Department of Pathology, University of Szeged, Szeged, Hungary
| | - Peter Horvath
- Synthetic and Systems Biology Unit, Biological Research Centre, Eötvös Loránd Research Network, Szeged, Hungary
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Single-Cell Technologies, Inc., Szeged, Hungary
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10
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Cui H, Wu Q, Zhao Z, Wang Y, Lu H. Selective Capture-Based Single-Cell Mass Spectrometry for Enhancing Sphingolipid Profiling of Neurons with Differentiation of Cell Body from Synapse. Anal Chem 2022; 94:15729-15737. [DOI: 10.1021/acs.analchem.2c03336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Hao Cui
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P.R. China
| | - Qian Wu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P.R. China
| | - Zhihao Zhao
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P.R. China
| | - Yang Wang
- Laboratory of Ethnopharmacology, Institute of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Hunan, Changsha 410008, P.R. China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Hunan, Changsha 410083, P.R. China
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11
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Zhang D, Qin Q, Qiao L. Mass spectrometry profiling of single bacterial cells reveals metabolic regulation during antibiotics induced bacterial filamentation. CHINESE CHEM LETT 2022. [DOI: 10.1016/j.cclet.2022.107938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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12
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Nguyen TD, Lan Y, Kane SS, Haffner JJ, Liu R, McCall LI, Yang Z. Single-Cell Mass Spectrometry Enables Insight into Heterogeneity in Infectious Disease. Anal Chem 2022; 94:10567-10572. [PMID: 35863111 PMCID: PMC10064790 DOI: 10.1021/acs.analchem.2c02279] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Cellular heterogeneity is generally overlooked in infectious diseases. In this study, we investigated host cell heterogeneity during infection with Trypanosoma cruzi (T. cruzi) parasites, causative agents of Chagas disease (CD). In chronic-stage CD, only a few host cells are infected with a large load of parasites and symptoms may appear at sites distal to parasite colonization. Furthermore, recent work has revealed T. cruzi heterogeneity with regard to replication rates and drug susceptibility. However, the role of cellular-level metabolic heterogeneity in these processes has yet to be assessed. To fill this knowledge gap, we developed a Single-probe SCMS (single-cell mass spectrometry) method compatible with biosafety protocols, to acquire metabolomics data from individual cells during T. cruzi infection. This study revealed heterogeneity in the metabolic response of the host cells to T. cruzi infection in vitro. Our results showed that parasite-infected cells possessed divergent metabolism compared to control cells. Strikingly, some uninfected cells adjacent to infected cells showed metabolic impacts as well. Specific metabolic changes include increases in glycerophospholipids with infection. These results provide novel insight into the pathogenesis of CD. Furthermore, they represent the first application of bioanalytical SCMS to the study of mammalian-infectious agents, with the potential for broad applications to study infectious diseases.
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Affiliation(s)
- Tra D Nguyen
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Yunpeng Lan
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Shelley S Kane
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Jacob J Haffner
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, Oklahoma 73019, United States.,Department of Anthropology, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Renmeng Liu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Laura-Isobel McCall
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.,Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, Oklahoma 73019, United States.,Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
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13
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Chen X, Peng Z, Yang Z. Metabolomics studies of cell-cell interactions using single cell mass spectrometry combined with fluorescence microscopy. Chem Sci 2022; 13:6687-6695. [PMID: 35756524 PMCID: PMC9172575 DOI: 10.1039/d2sc02298b] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 05/15/2022] [Indexed: 11/21/2022] Open
Abstract
Cell-cell interactions are critical for transmitting signals among cells and maintaining their normal functions from the single-cell level to tissues. In cancer studies, interactions between drug-resistant and drug-sensitive cells play an important role in the development of chemotherapy resistance of tumors. As metabolites directly reflect the cell status, metabolomics studies provide insight into cell-cell communication. Mass spectrometry (MS) is a powerful tool for metabolomics studies, and single cell MS (SCMS) analysis can provide unique information for understanding interactions among heterogeneous cells. In the current study, we utilized a direct co-culture system (with cell-cell contact) to study metabolomics of single cells affected by cell-cell interactions in their living status. A fluorescence microscope was utilized to distinguish these two types of cells for SCMS metabolomics studies using the Single-probe SCMS technique under ambient conditions. Our results show that through interactions with drug-resistant cells, drug-sensitive cancer cells acquired significantly increased drug resistance and exhibited drastically altered metabolites. Further investigation found that the increased drug resistance was associated with multiple metabolism regulations in drug-sensitive cells through co-culture such as the upregulation of sphingomyelins lipids and lactic acid and the downregulation of TCA cycle intermediates. The method allows for direct MS metabolomics studies of individual cells labeled with fluorescent proteins or dyes among heterogeneous populations.
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Affiliation(s)
- Xingxiu Chen
- Chemistry and Biochemistry Department, University of Oklahoma Norman Oklahoma 73072 USA
| | - Zongkai Peng
- Chemistry and Biochemistry Department, University of Oklahoma Norman Oklahoma 73072 USA
| | - Zhibo Yang
- Chemistry and Biochemistry Department, University of Oklahoma Norman Oklahoma 73072 USA
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14
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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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15
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Sun M, Chen X, Yang Z. Single cell mass spectrometry studies reveal metabolomic features and potential mechanisms of drug-resistant cancer cell lines. Anal Chim Acta 2022; 1206:339761. [PMID: 35473873 PMCID: PMC9046687 DOI: 10.1016/j.aca.2022.339761] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 03/18/2022] [Accepted: 03/22/2022] [Indexed: 12/28/2022]
Abstract
Irinotecan (Iri) is a key drug to treat metastatic colorectal cancer, but its clinical activity is often limited by de novo and acquired drug resistance. Studying the underlying mechanisms of drug resistance is necessary for developing novel therapeutic strategies. In this study, we used both regular and irinotecan-resistant (Iri-resistant) colorectal cell lines as models, and performed single cell mass spectrometry (SCMS) metabolomics studies combined with analyses from cytotoxicity assay, western blot, flow cytometry, quantitative real-time polymerase chain reaction (qPCR), and reactive oxygen species (ROS). Our SCMS results indicate that Iri-resistant cancer cells possess higher levels of unsaturated lipids compared with the regular cancer cells. In addition, multiple protein biomarkers and their corresponding mRNAs of colon cancer stem cells are overexpressed in Iri-resistance cells. Particularly, stearoyl-CoA desaturase 1 (SCD1) is upregulated with the development of drug resistance in Iri-resistant cells, whereas inhibiting the activity of SCD1 efficiently increase their sensitivity to Iri treatment. In addition, we demonstrated that SCD1 directly regulates the expression of ALDH1A1, which contributes to the cancer stemness and ROS level in Iri-resistant cell lines.
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16
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Chen X, Sun M, Yang Z. Single cell mass spectrometry analysis of drug-resistant cancer cells: Metabolomics studies of synergetic effect of combinational treatment. Anal Chim Acta 2022; 1201:339621. [PMID: 35300794 PMCID: PMC8933618 DOI: 10.1016/j.aca.2022.339621] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 01/30/2022] [Accepted: 02/14/2022] [Indexed: 12/24/2022]
Abstract
Irinotecan (IRI), a topoisomerase I inhibitor blocking DNA synthesis, is a widely used chemotherapy drug for metastatic colorectal cancer. Despite being an effective chemotherapy drug, its clinical effectiveness is limited by both intrinsic and acquired drug resistance. Previous studies indicate IRI induces cancer stemness in irinotecan-resistant (IRI-resistant) cells. Metformin, an oral antidiabetic drug, was recently reported for anticancer effects, likely due to its selective killing of cancer stem cells (CSCs). Given IRI-resistant cells exhibiting high cancer stemness, we hypothesize metformin can sensitize IRI-resistant cells and rescue the therapeutic effect. In this work, we utilized the Single-probe mass spectrometry technique to analyze live IRI-resistant cells under different treatment conditions. We discovered that metformin treatment was associated with the downregulation of lipids and fatty acids, potentially through the inhibition of fatty acid synthase (FASN). Importantly, certain species can be only detected from cells in their living status. The level of synergistic effect of metformin and IRI in their co-treatment of IRI-resistant cells was evaluated using Chou-Talalay combinational index. Using enzymatic activity assay, we determined that the co-treatment exhibit the highest FASN inhibition compared with the mono-treatment of IRI or metformin. To our knowledge, this is the first single-cell MS metabolomics study demonstrating metformin-IRI synergistic effect overcoming drug resistance in IRI-resistant cells.
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17
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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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18
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Simon D, Oleschuk R. The liquid micro junction-surface sampling probe (LMJ-SSP); a versatile ambient mass spectrometry interface. Analyst 2021; 146:6365-6378. [PMID: 34553725 DOI: 10.1039/d1an00725d] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Ambient ionization methods have become important tools in mass spectrometry. The LMJ-SSP can significantly simplify/reduce lengthy sample preparation requirements associated with mass spectrometry analysis. Samples may be introduced through direct contact, insertion and droplet injection, enabling applications from drug discovery and surface analysis to tissue profiling and metabolic mapping. This review examines the underlying principles associated with the LMJ-SSP interface and highlights modifications of the original design that have extended its capability. We summarize different application areas that have exploited the method and describe potential future directions for the adaptable ambient ionization source.
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Affiliation(s)
- David Simon
- Department of Chemistry, Queen's University, Kingston, Ontario, K7L 3N6, Canada.
| | - Richard Oleschuk
- Department of Chemistry, Queen's University, Kingston, Ontario, K7L 3N6, Canada.
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19
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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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20
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Zhang Q, Feng S, Lin L, Mao S, Lin JM. Emerging open microfluidics for cell manipulation. Chem Soc Rev 2021; 50:5333-5348. [PMID: 33972984 DOI: 10.1039/d0cs01516d] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Cell manipulation is the foundation of biochemical studies, which demands user-friendly, multifunctional and precise tools. Based on flow confinement principles, open microfluidics can control the movement of microscale liquid in open space. Every position of the circuit is accessible to external instruments, making it possible to perform precise treatment and analysis of cells at arbitrary target positions especially at the single-cell/sub-cell level. Benefiting from its unique superiority, various manipulations including patterned cell culture, 3D tissue modelling, localized chemical stimulation, online cellular factor analysis, single cell sampling, partial cell treatment, and subcellular free radical attack can be easily realized. In this tutorial review, we summarize two basic ideas to design open microfluidics: open microfluidic networks and probes. The principles of mainstream open microfluidic methods are explained, and their recent important applications are introduced. Challenges and developing trends of open microfluidics are also discussed.
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Affiliation(s)
- Qiang Zhang
- Department of Chemistry, Beijing Key Laboratory of Microanalytical Methods and Instrumentation, MOE Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Tsinghua University, Beijing, 100084, China.
| | - Shuo Feng
- Department of Chemistry, Beijing Key Laboratory of Microanalytical Methods and Instrumentation, MOE Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Tsinghua University, Beijing, 100084, China.
| | - Ling Lin
- Department of Bioengineering, Beijing Technology and Business University, Beijing 100048, China.
| | - Sifeng Mao
- Department of Applied Chemistry, Graduate School of Urban Environmental Sciences, Tokyo Metropolitan University, Minamiohsawa, Hachioji, Tokyo 192-0397, Japan
| | - Jin-Ming Lin
- Department of Chemistry, Beijing Key Laboratory of Microanalytical Methods and Instrumentation, MOE Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Tsinghua University, Beijing, 100084, China.
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21
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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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22
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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: 68] [Impact Index Per Article: 22.7] [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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23
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Del Prete E, Facchiano A, Profumo A, Angelini C, Romano P. GeenaR: A Web Tool for Reproducible MALDI-TOF Analysis. Front Genet 2021; 12:635814. [PMID: 33854526 PMCID: PMC8039533 DOI: 10.3389/fgene.2021.635814] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 03/01/2021] [Indexed: 12/21/2022] Open
Abstract
Mass spectrometry is a widely applied technology with a strong impact in the proteomics field. MALDI-TOF is a combined technology in mass spectrometry with many applications in characterizing biological samples from different sources, such as the identification of cancer biomarkers, the detection of food frauds, the identification of doping substances in athletes’ fluids, and so on. The massive quantity of data, in the form of mass spectra, are often biased and altered by different sources of noise. Therefore, extracting the most relevant features that characterize the samples is often challenging and requires combining several computational methods. Here, we present GeenaR, a novel web tool that provides a complete workflow for pre-processing, analyzing, visualizing, and comparing MALDI-TOF mass spectra. GeenaR is user-friendly, provides many different functionalities for the analysis of the mass spectra, and supports reproducible research since it produces a human-readable report that contains function parameters, results, and the code used for processing the mass spectra. First, we illustrate the features available in GeenaR. Then, we describe its internal structure. Finally, we prove its capabilities in analyzing oncological datasets by presenting two case studies related to ovarian cancer and colorectal cancer. GeenaR is available at http://proteomics.hsanmartino.it/geenar/.
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Affiliation(s)
- Eugenio Del Prete
- Institute for Applied Mathematics, National Research Council, Naples, Italy
| | - Angelo Facchiano
- Institute of Food Sciences, National Research Council, Avellino, Italy
| | - Aldo Profumo
- Proteomica e Spettrometria di Massa, IRCCS Ospedale Policlinico San Martino IST, Genova, Italy
| | - Claudia Angelini
- Institute for Applied Mathematics, National Research Council, Naples, Italy
| | - Paolo Romano
- Proteomica e Spettrometria di Massa, IRCCS Ospedale Policlinico San Martino IST, Genova, Italy
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24
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Bensen RC, Standke SJ, Colby DH, Kothapalli NR, Le-McClain AT, Patten MA, Tripathi A, Heinlen JE, Yang Z, Burgett AWG. Single Cell Mass Spectrometry Quantification of Anticancer Drugs: Proof of Concept in Cancer Patients. ACS Pharmacol Transl Sci 2021; 4:96-100. [PMID: 33615163 DOI: 10.1021/acsptsci.0c00156] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Indexed: 11/30/2022]
Abstract
In clinical cancer medicine, the current inability to quantify intracellular chemotherapy drug concentrations in individual human cells limits the personalization and overall effectiveness of drug administration. New bioanalytical methods capable of real-time measurement of drug levels in live single cancer cells would allow for more adaptive and personalized administration of chemotherapy drugs, potentially leading to better clinical outcomes with fewer side effects. In this study, we report the development of a new quantitative single cell mass spectrometry (qSCMS) method capable of providing absolute drug amounts and concentrations in single cancer cells. Using this qSCMS system, quantitative analysis of the intracellular drug gemcitabine present in individual bladder cancer cells is reported, including in bladder cancer cells isolated from patients undergoing standard-of-care gemcitabine chemotherapy. The development of single cell pharmacology bioanalytical methods can potentially lead to more effective and safely administered drug medications in patients, especially in the treatment of cancer.
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Affiliation(s)
- Ryan C Bensen
- Department of Chemistry & Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Shawna J Standke
- Department of Chemistry & Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Devon H Colby
- Department of Chemistry & Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Naga Rama Kothapalli
- Department of Chemistry & Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Anh T Le-McClain
- Department of Chemistry & Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Michael A Patten
- Oklahoma Biological Survey, University of Oklahoma, 111 E. Chesapeake Street, Norman, Oklahoma 73019, United States
| | - Abhishek Tripathi
- Stephenson Cancer Center, Section of Hematology Oncology, University of Oklahoma Health Sciences Center; 800 NE 10th Street, Oklahoma City, Oklahoma 73104, United States
| | - Jonathan E Heinlen
- Department of Urology, University of Oklahoma Health Sciences Center, 920 Stanton L. Young Boulevard, Oklahoma City, Oklahoma 73104, United States
| | - Zhibo Yang
- Department of Chemistry & Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Anthony W G Burgett
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Oklahoma Health Sciences Center, 1110 N. Stonewall Avenue, Oklahoma City, Oklahoma 73117, United States
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25
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Papantoniou I, Nilsson Hall G, Loverdou N, Lesage R, Herpelinck T, Mendes L, Geris L. Turning Nature's own processes into design strategies for living bone implant biomanufacturing: a decade of Developmental Engineering. Adv Drug Deliv Rev 2021; 169:22-39. [PMID: 33290762 PMCID: PMC7839840 DOI: 10.1016/j.addr.2020.11.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 11/20/2020] [Accepted: 11/29/2020] [Indexed: 12/14/2022]
Abstract
A decade after the term developmental engineering (DE) was coined to indicate the use of developmental processes as blueprints for the design and development of engineered living implants, a myriad of proof-of-concept studies demonstrate the potential of this approach in small animal models. This review provides an overview of DE work, focusing on applications in bone regeneration. Enabling technologies allow to quantify the distance between in vitro processes and their developmental counterpart, as well as to design strategies to reduce that distance. By embedding Nature's robust mechanisms of action in engineered constructs, predictive large animal data and subsequent positive clinical outcomes can be gradually achieved. To this end, the development of next generation biofabrication technologies should provide the necessary scale and precision for robust living bone implant biomanufacturing.
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Affiliation(s)
- Ioannis Papantoniou
- Institute of Chemical Engineering Sciences, Foundation for Research and Technology - Hellas (FORTH), Stadiou street, 26504 Patras, Greece; Skeletal Biology & Engineering Research Center, KU Leuven, Herestraat 49 (813), 3000 Leuven, Belgium; Prometheus, The KU Leuven R&D Division for Skeletal Tissue Engineering, Herestraat 49 (813), 3000 Leuven, Belgium.
| | - Gabriella Nilsson Hall
- Skeletal Biology & Engineering Research Center, KU Leuven, Herestraat 49 (813), 3000 Leuven, Belgium; Prometheus, The KU Leuven R&D Division for Skeletal Tissue Engineering, Herestraat 49 (813), 3000 Leuven, Belgium.
| | - Niki Loverdou
- Prometheus, The KU Leuven R&D Division for Skeletal Tissue Engineering, Herestraat 49 (813), 3000 Leuven, Belgium; GIGA in silico medicine, University of Liège, Avenue de l'Hôpital 11 (B34), 4000 Liège, Belgium; Biomechanics Section, KU Leuven, Celestijnenlaan 300C (2419), 3001 Leuven, Belgium.
| | - Raphaelle Lesage
- Prometheus, The KU Leuven R&D Division for Skeletal Tissue Engineering, Herestraat 49 (813), 3000 Leuven, Belgium; Biomechanics Section, KU Leuven, Celestijnenlaan 300C (2419), 3001 Leuven, Belgium.
| | - Tim Herpelinck
- Skeletal Biology & Engineering Research Center, KU Leuven, Herestraat 49 (813), 3000 Leuven, Belgium; Prometheus, The KU Leuven R&D Division for Skeletal Tissue Engineering, Herestraat 49 (813), 3000 Leuven, Belgium.
| | - Luis Mendes
- Skeletal Biology & Engineering Research Center, KU Leuven, Herestraat 49 (813), 3000 Leuven, Belgium; Prometheus, The KU Leuven R&D Division for Skeletal Tissue Engineering, Herestraat 49 (813), 3000 Leuven, Belgium.
| | - Liesbet Geris
- Skeletal Biology & Engineering Research Center, KU Leuven, Herestraat 49 (813), 3000 Leuven, Belgium; GIGA in silico medicine, University of Liège, Avenue de l'Hôpital 11 (B34), 4000 Liège, Belgium; Prometheus, The KU Leuven R&D Division for Skeletal Tissue Engineering, Herestraat 49 (813), 3000 Leuven, Belgium; Biomechanics Section, KU Leuven, Celestijnenlaan 300C (2419), 3001 Leuven, Belgium.
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26
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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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27
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Snowden SG, Fernandes HJ, Kent J, Foskolou S, Tate P, Field SF, Metzakopian E, Koulman A. Development and Application of High-Throughput Single Cell Lipid Profiling: A Study of SNCA-A53T Human Dopamine Neurons. iScience 2020; 23:101703. [PMID: 33196026 PMCID: PMC7644967 DOI: 10.1016/j.isci.2020.101703] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 09/10/2020] [Accepted: 10/15/2020] [Indexed: 02/02/2023] Open
Abstract
Advances in single cell genomics and transcriptomics have shown that at tissue level there is complex cellular heterogeneity. To understand the effect of this inter-cell heterogeneity on metabolism it is essential to develop a single cell lipid profiling approach that allows the measurement of lipids in large numbers of single cells from a population. This will provide a functional readout of cell activity and membrane structure. Using liquid extraction surface analysis coupled with high-resolution mass spectrometry we have developed a high-throughput method for untargeted single cell lipid profiling. This technological advance highlighted the importance of cellular heterogeneity in the functional metabolism of individual human dopamine neurons, suggesting that A53T alpha-synuclein (SNCA) mutant neurons have impaired membrane function. These results demonstrate that this single cell lipid profiling platform can provide robust data that will expand the frontiers in biomedical research.
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Affiliation(s)
- Stuart G. Snowden
- Core Metabolomics and Lipidomics Laboratory, Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Level 4 Pathology, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK,Department of Biological Sciences, Royal Holloway University of London, Egham, Surrey Tw20 0EX, UK
| | - Hugo J.R. Fernandes
- UK Dementia Research Institute, University of Cambridge, Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK
| | - Josh Kent
- Core Metabolomics and Lipidomics Laboratory, Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Level 4 Pathology, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK,UK Dementia Research Institute, University of Cambridge, Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK
| | - Stefanie Foskolou
- UK Dementia Research Institute, University of Cambridge, Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK
| | - Peri Tate
- Department of Biological Sciences, Royal Holloway University of London, Egham, Surrey Tw20 0EX, UK
| | - Sarah F. Field
- UK Dementia Research Institute, University of Cambridge, Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK
| | - Emmanouil Metzakopian
- UK Dementia Research Institute, University of Cambridge, Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK,Corresponding author
| | - Albert Koulman
- Core Metabolomics and Lipidomics Laboratory, Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Level 4 Pathology, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK,Corresponding author
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28
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Zhu Y, Wang W, Yang Z. Combining Mass Spectrometry with Paternò-Büchi Reaction to Determine Double-Bond Positions in Lipids at the Single-Cell Level. Anal Chem 2020; 92:11380-11387. [PMID: 32678580 PMCID: PMC7482314 DOI: 10.1021/acs.analchem.0c02245] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Single cell MS (SCMS) techniques are under rapid development for molecular analysis of individual cells among heterogeneous populations. Lipids are basic cellular constituents playing essential functions in energy storage and the cellular signaling processes of cells. Unsaturated lipids are characterized with one or multiple carbon-carbon double (C═C) bonds, and they are critical for cell functions and human diseases. Characterizing unsaturated lipids in single cells allows for better understanding of metabolomic biomarkers and therapeutic targets of rare cells (e.g., cancer stem cells); however, these studies remain challenging. We developed a new technique using a micropipette needle, in which Paternò-Büchi (PB) reactions at C═C bond can be induced, to determine locations of C═C bonds in unsaturated lipids at the single-cell level. The micropipette needle is produced by combining a pulled glass capillary needle with a fused silica capillary. Cell lysis solvent and PB reagent (acetone or benzophenone) are delivered into the micropipette needle (tip size ≈ 15 um) through a fused silica capillary. The capillary needle plays multiple functions (i.e., single cell sampling probe, cell lysis container, microreactor, and nano-ESI emitter) in the experiments. Both regular (no reaction) and reactive (with PB reaction) SCMS analyses of the same cell can be achieved. C═C bond locations were determined from MS scan and MS/MS of PB products assisted by Python programs. This technique can potentially be used for other reactive SCMS studies to enhance molecular analysis for broad ranges of single cells.
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Affiliation(s)
- Yanlin Zhu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Wenhua Wang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
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Cao YQ, Zhang L, Zhang J, Guo YL. Single-Cell On-Probe Derivatization-Noncontact Nanocarbon Fiber Ionization: Unraveling Cellular Heterogeneity of Fatty Alcohol and Sterol Metabolites. Anal Chem 2020; 92:8378-8385. [PMID: 32420735 DOI: 10.1021/acs.analchem.0c00954] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Currently in single-cell mass spectrometry, the analysis of low-abundance cell metabolites such as fatty alcohols and sterols remains a challenge. In most research studies, single-cell samples are analyzed directly after sampling. However, this workflow may exclude many effective sample pretreatment methods such as derivatization for the improvement of detection sensitivity for specific cell metabolites in a single-cell sample. Metabolites in low abundance in a cell may not be detected. Herein on-probe derivatization coupled with noncontact nanocarbon fiber ionization is proposed for sensitive fatty alcohol and sterol metabolite analysis at the single-cell level. Fatty alcohol and sterol metabolites were rapidly quaternized by the single-cell on-probe derivatization method. The reaction products were directly ionized with no postreaction processing. Furthermore, a new ionization source for noncontact nanocarbon fiber ionization was developed to show good compatibility with dichloromethane, a low-polarity solvent used in on-probe derivatization. The quaternized fatty alcohols and sterols exhibited evidently enhanced ionization efficiency in mass spectra. In applications of the developed method, seven kinds of even-numbered-carbon fatty alcohols (C12-C22) and five kinds of sterols were detected in single L-02 and HepG2 cells. Then the L-02 and HepG2 cells were readily discriminated through principal component analysis. Additionally, a rough quantitative analysis of the detected fatty alcohols and sterols in single cells was performed. The mass intensities of fatty alcohols show a significant difference between L-02 and HepG2 cells while those of sterols remain stable.
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Affiliation(s)
- Yu-Qi Cao
- State Key Laboratory of Organometallic Chemistry and National Center for Organic Mass Spectrometry in Shanghai, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, 200032, China
| | - Li Zhang
- State Key Laboratory of Organometallic Chemistry and National Center for Organic Mass Spectrometry in Shanghai, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, 200032, China
| | - Jing Zhang
- State Key Laboratory of Organometallic Chemistry and National Center for Organic Mass Spectrometry in Shanghai, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, 200032, China
| | - Yin-Long Guo
- State Key Laboratory of Organometallic Chemistry and National Center for Organic Mass Spectrometry in Shanghai, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, 200032, China
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30
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Wei X, Lu Y, Zhang X, Chen ML, Wang JH. Recent advances in single-cell ultra-trace analysis. Trends Analyt Chem 2020. [DOI: 10.1016/j.trac.2020.115886] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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31
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Zhang X, Wei X, Wei Y, Chen M, Wang J. The up-to-date strategies for the isolation and manipulation of single cells. Talanta 2020; 218:121147. [PMID: 32797903 DOI: 10.1016/j.talanta.2020.121147] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 05/07/2020] [Accepted: 05/08/2020] [Indexed: 02/06/2023]
Abstract
Due to the large cellular heterogeneity, the strategies for the isolation and manipulation of single cells have been pronounced indispensable in the fields of disease diagnostics, drug delivery, and cancer biology at the single-cell resolution. Herein, an overview of the up-to-date techniques for precise manipulation/separation and analysis of single-cell is accomplished, these include the various approaches for the isolation and detection of individual cells in flow cytometry, microfluidic systems, micromodule systems, and others. In addition, the advanced application of these protocols is discussed. In particular, a few designs are highlighted for visualization, non-invasion, and intelligentization in single cell analysis, i.e., imaging flow cytometry, label-free microfluidic platform, single-cell capillary probe, and other related techniques. At the present, the main barriers in the various schemes for single cell manipulation which limited their practical applications are their cumbersome construction and single-functionality. The future opportunities and outstanding challenges in the isolation/manipulation of single cells are depicted.
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Affiliation(s)
- Xuan Zhang
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang, Liaoning, 110819, China
| | - Xing Wei
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang, Liaoning, 110819, China
| | - Yujia Wei
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang, Liaoning, 110819, China
| | - Mingli Chen
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang, Liaoning, 110819, China; Analytical and Testing Center, Northeastern University, Shenyang, Liaoning, 110819, China.
| | - Jianhua Wang
- Research Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang, Liaoning, 110819, China.
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32
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Le NH, Ye G, Peng C, Chen JIL. Metabolic mapping with plasmonic nanoparticle assemblies. Analyst 2020; 145:2586-2594. [PMID: 32182299 DOI: 10.1039/c9an02262g] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
A rapid and simple methodology for the biomolecular analysis of single cells and microenvironments via a stick-and-peel plasmonic sensing platform is reported. Substrate-bound assemblies of plasmonic gold nanoparticles linked by reconfigurable oligonucleotides undergo disassembly upon target binding. Changes in the light scattering intensity of thousands of discrete nanoparticle assemblies are extrapolated concomitantly to yield the mapping of local target concentrations. The methodology is completely free of labelling, purification and separation steps. We quantified the intracellular ATP levels for two ovarian cancer cell lines to elucidate the differences and cellular distribution, and demonstrated the potential of the stick-and-peel platform for mapping the microenvironment of a 2D heterogeneous surface. The portable and economical analytical platform may broaden the affordability and applicability of single-cell based analyses and enable new opportunities in clinical care such as on-site molecular pathology.
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Affiliation(s)
- Nguyen H Le
- Department of Chemistry, York University, 4700 Keele Street, Toronto, Ontario M3J 1P3, Canada.
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Fernández-García J, Altea-Manzano P, Pranzini E, Fendt SM. Stable Isotopes for Tracing Mammalian-Cell Metabolism In Vivo. Trends Biochem Sci 2020; 45:185-201. [PMID: 31955965 DOI: 10.1016/j.tibs.2019.12.002] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Revised: 12/11/2019] [Accepted: 12/12/2019] [Indexed: 02/07/2023]
Abstract
Metabolism is at the cornerstone of all cellular functions and mounting evidence of its deregulation in different diseases emphasizes the importance of a comprehensive understanding of metabolic regulation at the whole-organism level. Stable-isotope measurements are a powerful tool for probing cellular metabolism and, as a result, are increasingly used to study metabolism in in vivo settings. The additional complexity of in vivo metabolic measurements requires paying special attention to experimental design and data interpretation. Here, we review recent work where in vivo stable-isotope measurements have been used to address relevant biological questions within an in vivo context, summarize different experimental and data interpretation approaches and their limitations, and discuss future opportunities in the field.
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Affiliation(s)
- Juan Fernández-García
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium.
| | - Patricia Altea-Manzano
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium
| | - Erica Pranzini
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium; Department of Experimental and Clinical Biomedical Sciences, University of Florence, Viale Morgagni 50, 50134 Florence, Italy
| | - Sarah-Maria Fendt
- Laboratory of Cellular Metabolism and Metabolic Regulation, VIB-KU Leuven Center for Cancer Biology, VIB, Herestraat 49, 3000 Leuven, Belgium; Laboratory of Cellular Metabolism and Metabolic Regulation, Department of Oncology, KU Leuven and Leuven Cancer Institute (LKI), Herestraat 49, 3000 Leuven, Belgium.
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Liu R, Sun M, Zhang G, Lan Y, Yang Z. Towards early monitoring of chemotherapy-induced drug resistance based on single cell metabolomics: Combining single-probe mass spectrometry with machine learning. Anal Chim Acta 2019; 1092:42-48. [PMID: 31708031 PMCID: PMC6878984 DOI: 10.1016/j.aca.2019.09.065] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 08/30/2019] [Accepted: 09/23/2019] [Indexed: 01/22/2023]
Abstract
Despite the presence of methods evaluating drug resistance during chemotherapies, techniques, which allow for monitoring the degree of drug resistance in early chemotherapeutic stage from single cells in their native microenvironment, are still absent. Herein, we report an analytical approach that combines single cell mass spectrometry (SCMS) based metabolomics with machine learning (ML) models to address the existing challenges. Metabolomic profiles of live cancer cells (HCT-116) with different levels (i.e., no, low, and high) of chemotherapy-induced drug resistance were measured using the Single-probe SCMS technique. A series of ML models, including random forest (RF), artificial neural network (ANN), and penalized logistic regression (LR), were constructed to predict the degrees of drug resistance of individual cells. A systematic comparison of performance was conducted among multiple models, and the method validation was carried out experimentally. Our results indicate that these ML models, especially the RF model constructed on the obtained SCMS datasets, can rapidly and accurately predict different degrees of drug resistance of live single cells. With such rapid and reliable assessment of drug resistance demonstrated at the single cell level, our method can be potentially employed to evaluate chemotherapeutic efficacy in the clinic.
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Affiliation(s)
- Renmeng Liu
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA
| | - Mei Sun
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA
| | - Genwei Zhang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA
| | - Yunpeng Lan
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA.
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35
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Zhu Y, Liu R, Yang Z. Redesigning the T-probe for mass spectrometry analysis of online lysis of non-adherent single cells. Anal Chim Acta 2019; 1084:53-59. [PMID: 31519234 PMCID: PMC6746249 DOI: 10.1016/j.aca.2019.07.059] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 07/25/2019] [Accepted: 07/28/2019] [Indexed: 12/16/2022]
Abstract
Single cell mass spectrometry (SCMS) allows for molecular analysis of individual cells while avoiding the inevitable drawbacks of using cell lysate prepared from populations of cells. Based on our previous design of the T-probe, a microscale sampling and ionization device for SCMS analysis, we further developed the device to perform online, and real time lysis of non-adherent live single cells for mass spectrometry (MS) analysis at ambient conditions. This redesigned T-probe includes three parts: a sampling probe with a small tip to withdraw a whole cell, a solvent-providing capillary to deliver lysis solution (i.e., acetonitrile), and a nano-ESI emitter in which rapid cell lysis and ionization occur followed by MS analysis. These three components are embedded between two polycarbonate slides and are jointed through a T-junction to form an integrated device. Colon cancer cells (HCT-116) under control and treatment (using anticancer drug irinotecan) conditions were analyzed. We detected a variety of intracellular species, and structural identification of selected ions was conducted using tandem MS (MS2). We further conducted statistical analysis (e.g., PLS-DA and t-test) to gain biological insights of cellular metabolism. Our results indicate that the influence of anticancer drugs on cellular metabolism of live non-adherent cells can be obtained using the SCMS experiments combined with statistical data analysis.
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Affiliation(s)
- Yanlin Zhu
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA
| | - Renmeng Liu
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA.
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36
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Tian X, Xie B, Zou Z, Jiao Y, Lin LE, Chen CL, Hsu CC, Peng J, Yang Z. Multimodal Imaging of Amyloid Plaques: Fusion of the Single-Probe Mass Spectrometry Image and Fluorescence Microscopy Image. Anal Chem 2019; 91:12882-12889. [PMID: 31536324 PMCID: PMC6885010 DOI: 10.1021/acs.analchem.9b02792] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. The formation of amyloid plaques by aggregated amyloid beta (Aβ) peptides is a primary event in AD pathology. Understanding the metabolomic features and related pathways is critical for studying plaque-related pathological events (e.g., cell death and neuron dysfunction). Mass spectrometry imaging (MSI), due to its high sensitivity and ability to obtain the spatial distribution of metabolites, has been applied to AD studies. However, limited studies of metabolites in amyloid plaques have been performed due to the drawbacks of the commonly used techniques such as matrix-assisted laser desorption/ionization MSI. In the current study, we obtained high spatial resolution (∼17 μm) MS images of the AD mouse brain using the Single-probe, a microscale sampling and ionization device, coupled to a mass spectrometer under ambient conditions. The adjacent slices were used to obtain fluorescence microscopy images to locate amyloid plaques. The MS image and the fluorescence microscopy image were fused to spatially correlate histological protein hallmarks with metabolomic features. The fused images produced significantly improved spatial resolution (∼5 μm), allowing for the determination of fine structures in MS images and metabolomic biomarkers representing amyloid plaques.
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Affiliation(s)
- Xiang Tian
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Boer Xie
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Zhu Zou
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Yun Jiao
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Li-En Lin
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Chih-Lin Chen
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Cheng-Chih Hsu
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
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37
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Liu R, Zhang G, Sun M, Pan X, Yang Z. Integrating a generalized data analysis workflow with the Single-probe mass spectrometry experiment for single cell metabolomics. Anal Chim Acta 2019; 1064:71-79. [PMID: 30982520 PMCID: PMC6579046 DOI: 10.1016/j.aca.2019.03.006] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 03/04/2019] [Accepted: 03/05/2019] [Indexed: 01/18/2023]
Abstract
We conducted single cell metabolomics studies of live cancer cells through online single cell mass spectrometry (SCMS) experiments combined with a generalized comprehensive data analysis workflow. The SCMS experiments were carried out using the Single-probe device coupled with a mass spectrometer to measure molecular profiles of cells in response to two mitotic inhibitors, taxol and vinblastine, under a series of treatment conditions. SCMS metabolomic data were analyzed using a comprehensive approach, including data pre-treatment, visualization, statistical analysis, machine learning, and pathway enrichment analysis. For comparative studies, traditional liquid chromatography-MS (LC-MS) experiments were conducted using lysates prepared from bulk cell samples. Metabolomic profiles of single cells were visualized through Partial Least Square-Discriminant Analysis (PLS-DA), and the phenotypic biomarkers associated with emerging phenotypes induced by drug treatment were discovered and compared through a series of rigorous statistical analysis. Species of interest were further identified at both the single cell and population levels. In addition, four biological pathways potentially involved in the drug treatment were determined through pathway enrichment analysis. Our work demonstrated the capability of comprehensive pipeline studies of single cell metabolomics. This method can be potentially applied to broader types of SCMS datasets for future pharmaceutical and chemotherapeutic research.
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Affiliation(s)
- Renmeng Liu
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA
| | - Genwei Zhang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA
| | - Mei Sun
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA
| | - Xiaoliang Pan
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, OK, 73019, USA.
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38
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Pan N, Standke SJ, Kothapalli NR, Sun M, Bensen RC, Burgett AWG, Yang Z. Quantification of Drug Molecules in Live Single Cells Using the Single-Probe Mass Spectrometry Technique. Anal Chem 2019; 91:9018-9024. [PMID: 31246408 PMCID: PMC6677389 DOI: 10.1021/acs.analchem.9b01311] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Analyzing cellular constituents on the single-cell level through mass spectrometry (MS) allows for a wide range of compounds to be studied simultaneously. However, there is a need for quantitative single-cell mass spectrometry (qSCMS) methods to fully characterize drug efficacy from individual cells within cell populations. In this study, qSCMS experiments were carried out using the Single-probe MS technique. The method was successfully used to perform rapid absolute quantifications of the anticancer drug irinotecan in individual mammalian cancer cells under ambient conditions in real time. Traditional liquid chromatography/mass spectrometry (LC/MS) quantifications of irinotecan in cell lysate samples were used to compare the results from Single-probe qSCMS. This technique showcases heterogeneity of drug efficacy on the single-cell level.
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Affiliation(s)
- Ning Pan
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Shawna J. Standke
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Naga Rama Kothapalli
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Mei Sun
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Ryan C. Bensen
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Anthony W. G. Burgett
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
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Standke SJ, Colby DH, Bensen RC, Burgett AWG, Yang Z. Integrated Cell Manipulation Platform Coupled with the Single-probe for Mass Spectrometry Analysis of Drugs and Metabolites in Single Suspension Cells. J Vis Exp 2019. [PMID: 31282898 DOI: 10.3791/59875] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Single cell mass spectrometry (SCMS) enables sensitive detection and accurate analysis of broad ranges of cellular species on the individual-cell level. The single-probe, a microscale sampling and ionization device, can be coupled with a mass spectrometer for on-line, rapid SCMS analysis of cellular constituents under ambient conditions. Previously, the single-probe SCMS technique was primarily used to measure cells immobilized onto a substrate, limiting the types of cells for studies. In the current study, the single-probe SCMS technology has been integrated with a cell manipulation system, typically used for in vitro fertilization. This integrated cell manipulation and analysis platform uses a cell-selection probe to capture identified individual floating cells and transfer the cells to the single-probe tip for microscale lysis, followed by immediate mass spectrometry analysis. This capture and transfer process removes the cells from the surrounding solution prior to analysis, minimizing the introduction of matrix molecules in the mass spectrometry analysis. This integrated setup is capable of SCMS analysis of targeted patient-isolated cells present in body fluids samples (e.g., urine, blood, saliva, etc.), allowing for potential applications of SCMS analysis to human medicine and disease biology.
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Affiliation(s)
- Shawna J Standke
- Department of Chemistry and Biochemistry, University of Oklahoma
| | - Devon H Colby
- Department of Chemistry and Biochemistry, University of Oklahoma
| | - Ryan C Bensen
- Department of Chemistry and Biochemistry, University of Oklahoma
| | | | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma;
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Tian X, Zhang G, Zou Z, Yang Z. Anticancer Drug Affects Metabolomic Profiles in Multicellular Spheroids: Studies Using Mass Spectrometry Imaging Combined with Machine Learning. Anal Chem 2019; 91:5802-5809. [PMID: 30951294 PMCID: PMC6573030 DOI: 10.1021/acs.analchem.9b00026] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Multicellular spheroids (hereinafter referred to as spheroids) are 3D biological models. The metabolomic profiles inside spheroids provide crucial information reflecting the molecular phenotypes and microenvironment of cells. To study the influence of an anticancer drug on the spatially resolved metabolites, spheroids were cultured using HCT-116 colorectal cancer cells, treated with the anticancer drug Irinotecan under a series of time- and concentration-dependent conditions. The Single-probe mass spectrometry imaging (MSI) technique was utilized to conduct the experiments. The MSI data were analyzed using advanced data analysis methods to efficiently extract metabolomic information. Multivariate curve resolution alternating least square (MCR-ALS) was used to decompose each MS image into different components with grouped species. To improve the efficiency of data analysis, both supervised (Random Forest) and unsupervised (cluster large applications (CLARA)) machine learning (ML) methods were employed to cluster MS images according to their metabolomic features. Our results indicate that anticancer drug significantly affected the abundances of a variety of metabolites in different regions of spheroids. This integrated experiment and data analysis approach can facilitate the studies of metabolites in different types of 3D tumor models and tissues and potentially benefit the drug discovery, therapeutic resistance, and other biological research fields.
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Affiliation(s)
- Xiang Tian
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Genwei Zhang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Zhu Zou
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
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