51
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Optical Microscopy-Guided Laser Ablation Electrospray Ionization Ion Mobility Mass Spectrometry: Ambient Single Cell Metabolomics with Increased Confidence in Molecular Identification. Metabolites 2021; 11:metabo11040200. [PMID: 33801673 PMCID: PMC8065410 DOI: 10.3390/metabo11040200] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 03/23/2021] [Accepted: 03/25/2021] [Indexed: 12/13/2022] Open
Abstract
Single cell analysis is a field of increasing interest as new tools are continually being developed to understand intercellular differences within large cell populations. Laser-ablation electrospray ionization mass spectrometry (LAESI-MS) is an emerging technique for single cell metabolomics. Over the years, it has been validated that this ionization technique is advantageous for probing the molecular content of individual cells in situ. Here, we report the integration of a microscope into the optical train of the LAESI source to allow for visually informed ambient in situ single cell analysis. Additionally, we have coupled this ‘LAESI microscope’ to a drift-tube ion mobility mass spectrometer to enable separation of isobaric species and allow for the determination of ion collision cross sections in conjunction with accurate mass measurements. This combined information helps provide higher confidence for structural assignment of molecules ablated from single cells. Here, we show that this system enables the analysis of the metabolite content of Allium cepa epidermal cells with high confidence structural identification together with their spatial locations within a tissue.
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52
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Bien T, Bessler S, Dreisewerd K, Soltwisch J. Transmission-Mode MALDI Mass Spectrometry Imaging of Single Cells: Optimizing Sample Preparation Protocols. Anal Chem 2021; 93:4513-4520. [PMID: 33646746 DOI: 10.1021/acs.analchem.0c04905] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) makes it possible to simultaneously visualize the spatial distribution of dozens to hundreds of different biomolecules (e.g., phospho- and glycolipids) in tissue sections and in cell cultures. The implementation of novel desorption and (post-)ionization techniques has recently pushed the pixel size of this imaging technique to the low micrometer scale and below and thus to a cellular and potentially sub-cellular level. However, to fully exploit this potential for cell biology and biomedicine, sample preparation becomes highly demanding. Here, we investigated the effect of several key parameters on the quality of the sample preparation and achievable spatial resolution, that include the washing, drying, chemical fixation, and matrix coating steps. The incubation of cells with formalin for about 5 min in combination with isotonic washing and mild drying produced a robust protocol that largely preserved not only cell morphologies, but also the molecular integrities of amine group-containing cell membrane phospholipids (phosphatidylethanolamines and -serines). A disadvantage of the chemical fixation is an increased permeabilization of cell membranes, resulting in leakage of cytosolic compounds. We demonstrate the pros and cons of the protocols with four model cell lines, cultured directly on indium tin oxide (ITO)-coated glass slides. Transmission (t-)mode MALDI-2-MSI enabled on a Q Exactive plus Orbitrap mass spectrometer was used to analyze the cultures at a pixel size of 2 μm. Phase contrast light microscopy and scanning electron microscopy were used as complementary methods. The protocols described could prove to be an important contribution to the advancement of single-cell MALDI imaging, especially for the characterization of cell-to-cell heterogeneities at a molecular level.
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Affiliation(s)
- Tanja Bien
- Institute of Hygiene, University of Münster, Robert-Koch-Str. 41, 48149 Münster, Germany.,Interdisciplinary Center for Clinical Research (IZKF), University of Münster, Domagkstr. 3, 48149 Münster, Germany
| | - Sebastian Bessler
- Institute of Hygiene, University of Münster, Robert-Koch-Str. 41, 48149 Münster, Germany
| | - Klaus Dreisewerd
- Institute of Hygiene, University of Münster, Robert-Koch-Str. 41, 48149 Münster, Germany.,Interdisciplinary Center for Clinical Research (IZKF), University of Münster, Domagkstr. 3, 48149 Münster, Germany
| | - Jens Soltwisch
- Institute of Hygiene, University of Münster, Robert-Koch-Str. 41, 48149 Münster, Germany.,Interdisciplinary Center for Clinical Research (IZKF), University of Münster, Domagkstr. 3, 48149 Münster, Germany
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53
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Liu R, Yang Z. Single cell metabolomics using mass spectrometry: Techniques and data analysis. Anal Chim Acta 2021; 1143:124-134. [PMID: 33384110 PMCID: PMC7775990 DOI: 10.1016/j.aca.2020.11.020] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 11/10/2020] [Accepted: 11/17/2020] [Indexed: 02/06/2023]
Abstract
Mass spectrometry (MS) based techniques are gaining popularity for metabolomics research due to their high sensitivity, wide detection range, and capability of molecular identification. Utilizing such powerful technique to explore the cellular metabolism at the single cell level not only appreciates the subtle cell-to-cell difference (i.e., cell heterogeneity), but also gains biological merits corresponding to individual cells or small cell subpopulations. In this review article, we first briefly summarize recent advances in single cell MS experimental techniques, and then emphasize on the single cell metabolomics data analysis approaches. Through implementation of statistical analysis and more advanced data analysis methods, single cell metabolomics is expected to find more potential applications in the translational and clinical fields in the future.
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Affiliation(s)
- Renmeng Liu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA; Alliance Pharma. Inc., Malvern, PA, 19355, USA
| | - Zhibo Yang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA.
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54
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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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55
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Gwanyanya A, Godsmark CN, Kelly-Laubscher R. Ethanolamine: A Potential Promoiety with Additional Effects in the Brain. CNS & NEUROLOGICAL DISORDERS-DRUG TARGETS 2020; 21:108-117. [PMID: 33319663 DOI: 10.2174/1871527319999201211204645] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/14/2020] [Accepted: 09/11/2020] [Indexed: 11/22/2022]
Abstract
Ethanolamine is a bioactive molecule found in several cells, including those in the central nervous system (CNS). In the brain, ethanolamine and ethanolamine-related molecules have emerged as prodrug moieties that can promote drug movement across the blood-brain barrier. This improvement in the ability to target drugs to the brain may also mean that in the process ethanolamine concentrations in the brain are increased enough for ethanolamine to exert its own neurological ac-tions. Ethanolamine and its associated products have various positive functions ranging from cell signaling to molecular storage, and alterations in their levels have been linked to neurodegenerative conditions such as Alzheimer's disease. This mini-review focuses on the effects of ethanolamine in the CNS and highlights the possible implications of these effects for drug design.
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Affiliation(s)
- Asfree Gwanyanya
- Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town,. South Africa
| | - Christie Nicole Godsmark
- School of Public Health, College of Medicine and Health, University College Cork, Cork,. Ireland
| | - Roisin Kelly-Laubscher
- Department of Pharmacology and Therapeutics, School of Medicine, College of Medicine and Health, University College Cork, Cork,. Ireland
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56
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Neumann EK, Djambazova KV, Caprioli RM, Spraggins JM. Multimodal Imaging Mass Spectrometry: Next Generation Molecular Mapping in Biology and Medicine. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2020; 31:2401-2415. [PMID: 32886506 PMCID: PMC9278956 DOI: 10.1021/jasms.0c00232] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Imaging mass spectrometry has become a mature molecular mapping technology that is used for molecular discovery in many medical and biological systems. While powerful by itself, imaging mass spectrometry can be complemented by the addition of other orthogonal, chemically informative imaging technologies to maximize the information gained from a single experiment and enable deeper understanding of biological processes. Within this review, we describe MALDI, SIMS, and DESI imaging mass spectrometric technologies and how these have been integrated with other analytical modalities such as microscopy, transcriptomics, spectroscopy, and electrochemistry in a field termed multimodal imaging. We explore the future of this field and discuss forthcoming developments that will bring new insights to help unravel the molecular complexities of biological systems, from single cells to functional tissue structures and organs.
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Affiliation(s)
- Elizabeth K Neumann
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
| | - Katerina V Djambazova
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
| | - Richard M Caprioli
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
- Department of Pharmacology, Vanderbilt University, 2220 Pierce Avenue, Nashville, Tennessee 37232, United States
- Department of Medicine, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
| | - Jeffrey M Spraggins
- Department of Biochemistry, Vanderbilt University, 607 Light Hall, Nashville, Tennessee 37205, United States
- Mass Spectrometry Research Center, Vanderbilt University, 465 21st Avenue S #9160, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, 7330 Stevenson Center, Station B 351822, Nashville, Tennessee 37235, United States
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57
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Xu S, Liu M, Bai Y, Liu H. Multi-Dimensional Organic Mass Cytometry: Simultaneous Analysis of Proteins and Metabolites on Single Cells. Angew Chem Int Ed Engl 2020; 60:1806-1812. [PMID: 33085796 DOI: 10.1002/anie.202009682] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Indexed: 12/11/2022]
Abstract
Mass cytometry is attracting significant attention for enabling spatiotemporal high-throughput single-cell analysis. As the first demonstration of the simultaneous detection of single-cell proteins and untargeted metabolites, a multi-dimensional organic mass-cytometry system was established by a simple microfluidic chip connected to a nanoelectrospray mass spectrometer, providing useful heterogeneous information about the cells. A series of mass probes with online-dissociated mass tags were developed, ensuring the semi-quantification of cell-surface proteins and the compatibility of endogenous metabolite detection at the single-cell level. Six cell surface antigens and ≈100 metabolites from three ovarian-cancer cell types and two breast-cancer cell types were successfully monitored and contributed to highly sensitive and specific cell typing. Doxorubicin-resistant cancer-cell analysis confirmed the applications in distinguishing rare cell phenotypes. The proposed system is simple, extensible, and promising for cell typing, drug-resistance analysis of tumor cells, and clinical diagnosis and therapy at the single-cell level.
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Affiliation(s)
- Shuting Xu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, P. R. China
| | - Mingxia Liu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, P. R. China
| | - Yu Bai
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, P. R. China
| | - Huwei Liu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, P. R. China
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58
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Xu S, Liu M, Bai Y, Liu H. Multi‐Dimensional Organic Mass Cytometry: Simultaneous Analysis of Proteins and Metabolites on Single Cells. Angew Chem Int Ed Engl 2020. [DOI: 10.1002/ange.202009682] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Shuting Xu
- Beijing National Laboratory for Molecular Sciences Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education College of Chemistry and Molecular Engineering Peking University Beijing 100871 P. R. China
| | - Mingxia Liu
- Beijing National Laboratory for Molecular Sciences Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education College of Chemistry and Molecular Engineering Peking University Beijing 100871 P. R. China
| | - Yu Bai
- Beijing National Laboratory for Molecular Sciences Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education College of Chemistry and Molecular Engineering Peking University Beijing 100871 P. R. China
| | - Huwei Liu
- Beijing National Laboratory for Molecular Sciences Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education College of Chemistry and Molecular Engineering Peking University Beijing 100871 P. R. China
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59
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Yan X, Zhao X, Zhou Z, McKay A, Brunet A, Zare RN. Cell-Type-Specific Metabolic Profiling Achieved by Combining Desorption Electrospray Ionization Mass Spectrometry Imaging and Immunofluorescence Staining. Anal Chem 2020; 92:13281-13289. [PMID: 32880432 PMCID: PMC8782277 DOI: 10.1021/acs.analchem.0c02519] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Cell-type-specific metabolic profiling in tissue with heterogeneous composition has been of great interest across all mass spectrometry imaging (MSI) technologies. We report here a powerful new chemical imaging capability in desorption electrospray ionization (DESI) MSI, which enables cell-type-specific and in situ metabolic profiling in complex tissue samples. We accomplish this by combining DESI-MSI with immunofluorescence staining using specific cell-type markers. We take advantage of the variable frequency of each distinct cell type in the lateral septal nucleus (LSN) region of mouse forebrain. This allows computational deconvolution of the cell-type-specific metabolic profile in neurons and astrocytes by convex optimization-a machine learning method. Based on our approach, we observed 107 metabolites that show different distributions and intensities between astrocytes and neurons. We subsequently identified 23 metabolites using high-resolution mass spectrometry (MS) and tandem MS, which include small metabolites such as adenosine and N-acetylaspartate previously associated with astrocytes and neurons, respectively, as well as accumulation of several phospholipid species in neurons which have not been studied before. Overall, this method overcomes the relatively low spatial resolution of DESI-MSI and provides a new platform for in situ metabolic investigation at the cell-type level in complex tissue samples with heterogeneous cell-type composition.
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Affiliation(s)
- Xin Yan
- Department of Chemistry, Texas A&M University, College Station, TX 77843.; Department of Chemistry, Stanford University, Stanford, CA 94305, USA
| | - Xiaoai Zhao
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Zhenpeng Zhou
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA
| | - Andrew McKay
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Anne Brunet
- Glenn Laboratories for the Biology of Aging, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Richard N. Zare
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA
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60
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Fernandez RF, Ellis JM. Acyl-CoA synthetases as regulators of brain phospholipid acyl-chain diversity. Prostaglandins Leukot Essent Fatty Acids 2020; 161:102175. [PMID: 33031993 PMCID: PMC8693597 DOI: 10.1016/j.plefa.2020.102175] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 07/22/2020] [Accepted: 09/09/2020] [Indexed: 12/20/2022]
Abstract
Each individual cell-type is defined by its distinct morphology, phenotype, molecular and lipidomic profile. The importance of maintaining cell-specific lipidomic profiles is exemplified by the numerous diseases, disorders, and dysfunctional outcomes that occur as a direct result of altered lipidome. Therefore, the mechanisms regulating cellular lipidome diversity play a role in maintaining essential biological functions. The brain is an organ particularly rich in phospholipids, the main constituents of cellular membranes. The phospholipid acyl-chain profile of membranes in the brain is rather diverse due in part to the high degree of cellular heterogeneity. These membranes and the acyl-chain composition of their phospholipids are highly regulated, but the mechanisms that confer this tight regulation are incompletely understood. A family of enzymes called acyl-CoA synthetases (ACSs) stands at a pinnacle step allowing influence over cellular acyl-chain selection and subsequent metabolic flux. ACSs perform the initial reaction for cellular fatty acid metabolism by ligating a Coenzyme A to a fatty acid which both traps a fatty acid within a cell and activates it for metabolism. The ACS family of enzymes is large and diverse consisting of 25-26 family members that are nonredundant, each with unique distribution across and within cell types, and differential fatty acid substrate preferences. Thus, ACSs confer a critical intracellular fatty acid selecting step in a cell-type dependent manner providing acyl-CoA moieties that serve as essential precursors for phospholipid synthesis and remodeling, and therefore serve as a key regulator of cellular membrane acyl-chain compositional diversity. Here we will discuss how the contribution of individual ACSs towards brain lipid metabolism has only just begun to be elucidated and discuss the possibilities for how ACSs may differentially regulate brain lipidomic diversity.
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Affiliation(s)
- Regina F Fernandez
- Department of Physiology and East Carolina Diabetes and Obesity Institute, East Carolina University, Brody School of Medicine, NC, United States
| | - Jessica M Ellis
- Department of Physiology and East Carolina Diabetes and Obesity Institute, East Carolina University, Brody School of Medicine, NC, United States.
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61
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Ščupáková K, Dewez F, Walch AK, Heeren RMA, Balluff B. Morphometric Cell Classification for Single-Cell MALDI-Mass Spectrometry Imaging. Angew Chem Int Ed Engl 2020; 59:17447-17450. [PMID: 32668069 PMCID: PMC7540554 DOI: 10.1002/anie.202007315] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/04/2020] [Indexed: 12/14/2022]
Abstract
The large-scale and label-free molecular characterization of single cells in their natural tissue habitat remains a major challenge in molecular biology. We present a method that integrates morphometric image analysis to delineate and classify individual cells with their single-cell-specific molecular profiles. This approach provides a new means to study spatial biological processes such as cancer field effects and the relationship between morphometric and molecular features.
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Affiliation(s)
- Klára Ščupáková
- Maastricht MultiModal Molecular Imaging Institute (M4I)University of MaastrichtUniversiteitssingel 506200 MDMaastrichtThe Netherlands
| | - Frédéric Dewez
- Maastricht MultiModal Molecular Imaging Institute (M4I)University of MaastrichtUniversiteitssingel 506200 MDMaastrichtThe Netherlands
- Mass Spectrometry Laboratory (MSLab)University of LiègeBelgium
| | - Axel K. Walch
- Research Unit Analytical PathologyHelmholtz Zentrum MünchenOberschleißheimGermany
| | - Ron M. A. Heeren
- Maastricht MultiModal Molecular Imaging Institute (M4I)University of MaastrichtUniversiteitssingel 506200 MDMaastrichtThe Netherlands
| | - Benjamin Balluff
- Maastricht MultiModal Molecular Imaging Institute (M4I)University of MaastrichtUniversiteitssingel 506200 MDMaastrichtThe Netherlands
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62
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Ščupáková K, Dewez F, Walch AK, Heeren RMA, Balluff B. Morphometric Cell Classification for Single‐Cell MALDI‐Mass Spectrometry Imaging. Angew Chem Int Ed Engl 2020. [DOI: 10.1002/ange.202007315] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Klára Ščupáková
- Maastricht MultiModal Molecular Imaging Institute (M4I) University of Maastricht Universiteitssingel 50 6200 MD Maastricht The Netherlands
| | - Frédéric Dewez
- Maastricht MultiModal Molecular Imaging Institute (M4I) University of Maastricht Universiteitssingel 50 6200 MD Maastricht The Netherlands
- Mass Spectrometry Laboratory (MSLab) University of Liège Belgium
| | - Axel K. Walch
- Research Unit Analytical Pathology Helmholtz Zentrum München Oberschleißheim Germany
| | - Ron M. A. Heeren
- Maastricht MultiModal Molecular Imaging Institute (M4I) University of Maastricht Universiteitssingel 50 6200 MD Maastricht The Netherlands
| | - Benjamin Balluff
- Maastricht MultiModal Molecular Imaging Institute (M4I) University of Maastricht Universiteitssingel 50 6200 MD Maastricht The Netherlands
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63
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Xie YR, Castro DC, Bell SE, Rubakhin SS, Sweedler JV. Single-Cell Classification Using Mass Spectrometry through Interpretable Machine Learning. Anal Chem 2020; 92:9338-9347. [PMID: 32519839 PMCID: PMC7374983 DOI: 10.1021/acs.analchem.0c01660] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The brain consists of organized ensembles of cells that exhibit distinct morphologies, cellular connectivity, and dynamic biochemistries that control the executive functions of an organism. However, the relationships between chemical heterogeneity, cell function, and phenotype are not always understood. Recent advancements in matrix-assisted laser desorption/ionization mass spectrometry have enabled the high-throughput, multiplexed chemical analysis of single cells, capable of resolving hundreds of molecules in each mass spectrum. We developed a machine learning workflow to classify single cells according to their mass spectra based on cell groups of interest (GOI), e.g., neurons vs astrocytes. Three data sets from various cell groups were acquired on three different mass spectrometer platforms representing thousands of individual cell spectra that were collected and used to validate the single cell classification workflow. The trained models achieved >80% classification accuracy and were subjected to the recently developed instance-based model interpretation framework, SHapley Additive exPlanations (SHAP), which locally assigns feature importance for each single-cell spectrum. SHAP values were used for both local and global interpretations of our data sets, preserving the chemical heterogeneity uncovered by the single-cell analysis while offering the ability to perform supervised analysis. The top contributing mass features to each of the GOI were ranked and selected using mean absolute SHAP values, highlighting the features that are specific to the defined GOI. Our approach provides insight into discriminating the chemical profiles of the single cells through interpretable machine learning, facilitating downstream analysis and validation.
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Affiliation(s)
- Yuxuan Richard Xie
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
| | - Daniel C. Castro
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
| | - Sara E. Bell
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
| | - Stanislav S. Rubakhin
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
| | - Jonathan V. Sweedler
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
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64
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Huang P, Huang CY, Lin TC, Lin LE, Yang E, Lee C, Hsu CC, Chou PT. Toward the Rational Design of Universal Dual Polarity Matrix for MALDI Mass Spectrometry. Anal Chem 2020; 92:7139-7145. [PMID: 32314914 DOI: 10.1021/acs.analchem.0c00570] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
A series of novel anthranilic acid derivatives I-IV, of which COOH-NH2 (I) and COOH-NHMe (IV) are endowed with acid and base bifunctionality, were designed and synthesized for matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry applications in dual polarity molecular imaging of biological samples, particularly for lipids. The heat of protonation, deprotonation, and proton transfer reaction as well as the capability of analyzing biomolecules in both positive and negative ion modes for I-IV were systematically investigated under standard 355 nm laser excitation. The results indicate correlation between dual polarity and acid-base property. Further, COOH-NHMe (IV) showed a unique performance and was successfully applied as the matrix for MALDI-TOF mass spectrometry imaging (MSI) for studying the mouse brain. Our results demonstrate the superiority of COOH-NHMe (IV) in detecting more lipid and protein species compared to commercially available matrices. Moreover, MALDI-TOF MSI results were obtained for lipid distributions, making COOH-NHMe (IV) a potential next generation universal matrix.
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Affiliation(s)
- Penghsuan Huang
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan (R.O.C.)
| | - Chun-Ying Huang
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan (R.O.C.)
| | - Ta-Chun Lin
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan (R.O.C.)
| | - Li-En Lin
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan (R.O.C.)
| | - Ethan Yang
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan (R.O.C.).,Department of Chemistry, Université de Montréal, Montreal, Quebec Canada H3T 1J4
| | - Chuping Lee
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan (R.O.C.).,Department of Applied Chemistry, National Chiayi University, Chiayi City 60004, Taiwan (R.O.C.)
| | - Cheng-Chih Hsu
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan (R.O.C.)
| | - Pi-Tai Chou
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan (R.O.C.)
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65
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66
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Alexandrov T. Spatial Metabolomics and Imaging Mass Spectrometry in the Age of Artificial Intelligence. Annu Rev Biomed Data Sci 2020; 3:61-87. [PMID: 34056560 DOI: 10.1146/annurev-biodatasci-011420-031537] [Citation(s) in RCA: 107] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Spatial metabolomics is an emerging field of omics research that has enabled localizing metabolites, lipids, and drugs in tissue sections, a feat considered impossible just two decades ago. Spatial metabolomics and its enabling technology-imaging mass spectrometry-generate big hyper-spectral imaging data that have motivated the development of tailored computational methods at the intersection of computational metabolomics and image analysis. Experimental and computational developments have recently opened doors to applications of spatial metabolomics in life sciences and biomedicine. At the same time, these advances have coincided with a rapid evolution in machine learning, deep learning, and artificial intelligence, which are transforming our everyday life and promise to revolutionize biology and healthcare. Here, we introduce spatial metabolomics through the eyes of a computational scientist, review the outstanding challenges, provide a look into the future, and discuss opportunities granted by the ongoing convergence of human and artificial intelligence.
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Affiliation(s)
- Theodore Alexandrov
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany.,Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California 92093, USA
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Zhang W, Li N, Lin L, Huang Q, Uchiyama K, Lin JM. Concentrating Single Cells in Picoliter Droplets for Phospholipid Profiling on a Microfluidic System. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e1903402. [PMID: 31769602 DOI: 10.1002/smll.201903402] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 11/08/2019] [Indexed: 06/10/2023]
Abstract
Cellular membranes are composed of a variety of lipids in different amounts and proportions, and alterations of them are usually closely related to various diseases. To reveal the intercellular heterogeneity of the lipid variation, an integrated microfluidic system is designed, which consists of droplet-based inkjet printing, dielectrophoretic electrodes, and de-emulsification interface to achieve on-line single-cell encapsulation, manipulation, and mass spectrometry (MS) detection. This integrated system effectively improves the single-cell encapsulation rate, and meanwhile reduces the matrix interference and continuous oil phase interference to the MS detection. Using this system, the heterogeneities between the normal and cancer cells are compared, and the heterogeneity of the same cells before and after the drug treatment changed obviously, indicating that this system can be used as a promising tool for studying the link between the alterations of lipid homeostasis and various diseases.
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Affiliation(s)
- Weifei 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
| | - Nan Li
- 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
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
| | - Ling Lin
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, 100190, China
| | - Qiushi Huang
- 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
| | - Katsumi Uchiyama
- 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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De novo discovery of metabolic heterogeneity with immunophenotype-guided imaging mass spectrometry. Mol Metab 2020; 36:100953. [PMID: 32278304 PMCID: PMC7149754 DOI: 10.1016/j.molmet.2020.01.017] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 01/21/2020] [Accepted: 01/27/2020] [Indexed: 02/06/2023] Open
Abstract
Imaging mass spectrometry enables in situ label-free detection of thousands of metabolites from intact tissue samples. However, automated steps for multi-omics analyses and interpretation of histological images have not yet been implemented in mass spectrometry data analysis workflows. The characterization of molecular properties within cellular and histological features is done via time-consuming, non-objective, and irreproducible definitions of regions of interest, which are often accompanied by a loss of spatial resolution due to mass spectra averaging. Methods: We developed a new imaging pipeline called Spatial Correlation Image Analysis (SPACiAL), which is a computational multimodal workflow designed to combine molecular imaging data with multiplex immunohistochemistry (IHC). SPACiAL allows comprehensive and spatially resolved in situ correlation analyses on a cellular resolution. To demonstrate the method, matrix-assisted laser desorption-ionization (MALDI) Fourier-transform ion cyclotron resonance (FTICR) imaging mass spectrometry of metabolites and multiplex IHC staining were performed on the very same tissue section of mouse pancreatic islets and on human gastric cancer tissue specimens. The SPACiAL pipeline was used to perform an automatic, semantic-based, functional tissue annotation of histological and cellular features to identify metabolic profiles. Spatial correlation networks were generated to analyze metabolic heterogeneity associated with cellular features. Results: To demonstrate the new method, the SPACiAL pipeline was used to identify metabolic signatures of alpha and beta cells within islets of Langerhans, which are cell types that are not distinguishable via morphology alone. The semantic-based, functional tissue annotation allows an unprecedented analysis of metabolic heterogeneity via the generation of spatial correlation networks. Additionally, we demonstrated intra- and intertumoral metabolic heterogeneity within HER2/neu-positive and -negative gastric tumor cells. Conclusions: We developed the SPACiAL workflow to provide IHC-guided in situ metabolomics on intact tissue sections. Diminishing the workload by automated recognition of histological and functional features, the pipeline allows comprehensive analyses of metabolic heterogeneity. The multimodality of immunohistochemical staining and extensive molecular information from imaging mass spectrometry has the advantage of increasing both the efficiency and precision for spatially resolved analyses of specific cell types. The SPACiAL method is a stepping stone for the objective analysis of high-throughput, multi-omics data from clinical research and practice that is required for diagnostics, biomarker discovery, or therapy response prediction. Novel method enables phenotype-guided in situ metabolomics on intact tissue sections. Metabolic heterogeneity can be objectified under (patho-)physiological conditions. Innovative approach for tissue-based, preclinical, and clinical research.
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69
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Wang J, Han X. Analytical challenges of shotgun lipidomics at different resolution of measurements. Trends Analyt Chem 2019; 121:115697. [PMID: 32713986 PMCID: PMC7382544 DOI: 10.1016/j.trac.2019.115697] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The essence of shotgun lipidomics is to maintain consistency of the chemical environment of lipid samples during mass spectrometry acquisition. This strategy is suitable for large-scale quantitative analysis. This strategy also allows sufficient time to collect data to improve the signal-to-noise ratio. The initial approach of shotgun lipidomics was the electrospray ionization (ESI)-based direct infusion mass spectrometry strategy. With development of mass spectrometry for small molecules, shotgun lipidomics methods have been extended to matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) and ambient mass spectrometry, including MS imaging methods. Furthermore, the object of analysis has extended from organ and body fluid levels to tissue and cell levels with technological developments. In this article, we summarize the status and technical challenges of shotgun lipidomics at different resolution of measurements from the mass spectrometry perspective.
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Affiliation(s)
- Jianing Wang
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229 USA
| | - Xianlin Han
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229 USA
- Department of Medicine – Diabetes, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229 USA
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Tang S, Cheng H, Yan X. On‐Demand Electrochemical Epoxidation in Nano‐Electrospray Ionization Mass Spectrometry to Locate Carbon–Carbon Double Bonds. Angew Chem Int Ed Engl 2019; 59:209-214. [DOI: 10.1002/anie.201911070] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 10/03/2019] [Indexed: 12/31/2022]
Affiliation(s)
- Shuli Tang
- Department of Chemistry Texas A&M University 580 Ross St. College Station TX 77845 USA
| | - Heyong Cheng
- Department of Chemistry Texas A&M University 580 Ross St. College Station TX 77845 USA
- College of Material Chemistry and Chemical Engineering Hangzhou Normal University Hangzhou 311121 China
| | - Xin Yan
- Department of Chemistry Texas A&M University 580 Ross St. College Station TX 77845 USA
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On‐Demand Electrochemical Epoxidation in Nano‐Electrospray Ionization Mass Spectrometry to Locate Carbon–Carbon Double Bonds. Angew Chem Int Ed Engl 2019. [DOI: 10.1002/ange.201911070] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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72
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Chen W, Li S, Kulkarni AS, Huang L, Cao J, Qian K, Wan J. Single Cell Omics: From Assay Design to Biomedical Application. Biotechnol J 2019; 15:e1900262. [DOI: 10.1002/biot.201900262] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 09/11/2019] [Indexed: 12/21/2022]
Affiliation(s)
- Wenyi Chen
- School of Chemistry and Molecular EngineeringEast China Normal University Shanghai 200241 P. R. China
| | - Shumin Li
- School of Chemistry and Molecular EngineeringEast China Normal University Shanghai 200241 P. R. China
| | - Anuja Shreeram Kulkarni
- School of Biomedical EngineeringMed‐X Research InstituteShanghai Jiao Tong University Shanghai 200030 P. R. China
| | - Lin Huang
- School of Biomedical EngineeringMed‐X Research InstituteShanghai Jiao Tong University Shanghai 200030 P. R. China
| | - Jing Cao
- School of Biomedical EngineeringMed‐X Research InstituteShanghai Jiao Tong University Shanghai 200030 P. R. China
| | - Kun Qian
- School of Biomedical EngineeringMed‐X Research InstituteShanghai Jiao Tong University Shanghai 200030 P. R. China
| | - Jingjing Wan
- School of Chemistry and Molecular EngineeringEast China Normal University Shanghai 200241 P. R. China
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Neumann EK, Ellis JF, Triplett AE, Rubakhin SS, Sweedler JV. Lipid Analysis of 30 000 Individual Rodent Cerebellar Cells Using High-Resolution Mass Spectrometry. Anal Chem 2019; 91:7871-7878. [PMID: 31122012 DOI: 10.1021/acs.analchem.9b01689] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Single-cell measurements aid our understanding of chemically heterogeneous systems such as the brain. Lipids are one of the least studied chemical classes, and their cell-to-cell heterogeneity remains largely unexplored. We adapted microscopy-guided single-cell profiling using matrix-assisted laser desorption/ionization ion cyclotron resonance mass spectrometry to profile the lipid composition of over 30 000 individual rat cerebellar cells. We detected 520 lipid features, many of which were found in subsets of cells; Louvain clustering identified 101 distinct groups that can be correlated to neuronal and astrocytic classifications and lipid classes. Overall, the two most common lipids found were [PC(32:0)+H]+ and [PC(34:1)+H]+, which were present within 98.9 and 89.5% of cells, respectively; lipid signals present in <1% of cells were also detected, including [PC(34:1)+K]+ and [PG(40:2(OH))+Na]+. These results illustrate the vast lipid heterogeneity found within rodent cerebellar cells and hint at the distinct functional consequences of this heterogeneity.
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74
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Li Q, Tang F, Huo X, Huang X, Zhang Y, Wang X, Zhang X. Native State Single-Cell Printing System and Analysis for Matrix Effects. Anal Chem 2019; 91:8115-8122. [DOI: 10.1021/acs.analchem.9b00344] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Qi Li
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Fei Tang
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Xinming Huo
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Xi Huang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Yan Zhang
- Department of Electrical and Computer Engineering, University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United States
| | - Xiaohao Wang
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Xinrong Zhang
- Department of Chemistry, Tsinghua University, Beijing 100084, China
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