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Lin YS, Sun CL, Tsang S, Bensalem S, Le Pioufle B, Wang HY. Label-free and noninvasive analysis of microorganism surface epistructures at the single-cell level. Biophys J 2023; 122:1794-1806. [PMID: 37041747 PMCID: PMC10209039 DOI: 10.1016/j.bpj.2023.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 11/10/2022] [Accepted: 04/07/2023] [Indexed: 04/13/2023] Open
Abstract
Cell surface properties of microorganisms provide abundant information for their physiological status and fate choice. However, current methods for analyzing cell surface properties require labeling or fixation, which can alter the cell activity. This study establishes a label-free, rapid, noninvasive, and quantitative analysis of cell surface properties, including the presence and the dimension of epistructure, down to the single-cell level and at the nanometer scale. Simultaneously, electrorotation provides dielectric properties of intracellular contents. With the combined information, the growth phase of microalgae cells can be identified. The measurement is based on electrorotation of single cells, and an electrorotation model accounting for the surface properties is developed to properly interpret experimental data. The epistructure length measured by electrorotation is validated by scanning electron microscopy. The measurement accuracy is satisfactory in particular in the case of microscale epistructures in the exponential phase and nanoscale epistructures in the stationary phase. However, the measurement accuracy for nanoscale epistructures on cells in the exponential phase is offset by the effect of a thick double layer. Lastly, a diversity in epistructure length distinguishes exponential phase from stationary phase.
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Affiliation(s)
- Yu-Sheng Lin
- Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan; Université Paris Saclay, ENS Paris Saclay, CNRS Institut d'Alembert, SATIE, Gif sur Yvette, France
| | - Chen-Li Sun
- Department of Mechanical Engineering, National Taiwan University, Taipei, Taiwan
| | - Sung Tsang
- Department of Mechanical Engineering, National Taiwan University, Taipei, Taiwan
| | - Sakina Bensalem
- Université Paris Saclay, ENS Paris Saclay, CNRS Institut d'Alembert, LUMIN, Gif sur Yvette, France
| | - Bruno Le Pioufle
- Université Paris Saclay, ENS Paris Saclay, CNRS Institut d'Alembert, LUMIN, Gif sur Yvette, France
| | - Hsiang-Yu Wang
- Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan.
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2
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Advances in Mass Spectrometry-Based Single Cell Analysis. BIOLOGY 2023; 12:biology12030395. [PMID: 36979087 PMCID: PMC10045136 DOI: 10.3390/biology12030395] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/27/2023] [Accepted: 03/01/2023] [Indexed: 03/06/2023]
Abstract
Technological developments and improvements in single-cell isolation and analytical platforms allow for advanced molecular profiling at the single-cell level, which reveals cell-to-cell variation within the admixture cells in complex biological or clinical systems. This helps to understand the cellular heterogeneity of normal or diseased tissues and organs. However, most studies focused on the analysis of nucleic acids (e.g., DNA and RNA) and mass spectrometry (MS)-based analysis for proteins and metabolites of a single cell lagged until recently. Undoubtedly, MS-based single-cell analysis will provide a deeper insight into cellular mechanisms related to health and disease. This review summarizes recent advances in MS-based single-cell analysis methods and their applications in biology and medicine.
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3
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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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4
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Advances in Plant Metabolomics and Its Applications in Stress and Single-Cell Biology. Int J Mol Sci 2022; 23:ijms23136985. [PMID: 35805979 PMCID: PMC9266571 DOI: 10.3390/ijms23136985] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/19/2022] [Accepted: 06/19/2022] [Indexed: 02/04/2023] Open
Abstract
In the past two decades, the post-genomic era envisaged high-throughput technologies, resulting in more species with available genome sequences. In-depth multi-omics approaches have evolved to integrate cellular processes at various levels into a systems biology knowledge base. Metabolomics plays a crucial role in molecular networking to bridge the gaps between genotypes and phenotypes. However, the greater complexity of metabolites with diverse chemical and physical properties has limited the advances in plant metabolomics. For several years, applications of liquid/gas chromatography (LC/GC)-mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been constantly developed. Recently, ion mobility spectrometry (IMS)-MS has shown utility in resolving isomeric and isobaric metabolites. Both MS and NMR combined metabolomics significantly increased the identification and quantification of metabolites in an untargeted and targeted manner. Thus, hyphenated metabolomics tools will narrow the gap between the number of metabolite features and the identified metabolites. Metabolites change in response to environmental conditions, including biotic and abiotic stress factors. The spatial distribution of metabolites across different organs, tissues, cells and cellular compartments is a trending research area in metabolomics. Herein, we review recent technological advancements in metabolomics and their applications in understanding plant stress biology and different levels of spatial organization. In addition, we discuss the opportunities and challenges in multiple stress interactions, multi-omics, and single-cell metabolomics.
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5
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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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6
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Krejčí P, Cechová MZ, Nádvorníková J, Barták P, Kobrlová L, Balarynová J, Smýkal P, Bednář P. Combination of electronically driven micromanipulation with laser desorption ionization mass spectrometry – The unique tool for analysis of seed coat layers and revealing the mystery of seed dormancy. Talanta 2022; 242:123303. [DOI: 10.1016/j.talanta.2022.123303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 01/18/2022] [Accepted: 02/09/2022] [Indexed: 10/19/2022]
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7
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Moran MA, Kujawinski EB, Schroer WF, Amin SA, Bates NR, Bertrand EM, Braakman R, Brown CT, Covert MW, Doney SC, Dyhrman ST, Edison AS, Eren AM, Levine NM, Li L, Ross AC, Saito MA, Santoro AE, Segrè D, Shade A, Sullivan MB, Vardi A. Microbial metabolites in the marine carbon cycle. Nat Microbiol 2022; 7:508-523. [PMID: 35365785 DOI: 10.1038/s41564-022-01090-3] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 02/23/2022] [Indexed: 01/08/2023]
Abstract
One-quarter of photosynthesis-derived carbon on Earth rapidly cycles through a set of short-lived seawater metabolites that are generated from the activities of marine phytoplankton, bacteria, grazers and viruses. Here we discuss the sources of microbial metabolites in the surface ocean, their roles in ecology and biogeochemistry, and approaches that can be used to analyse them from chemistry, biology, modelling and data science. Although microbial-derived metabolites account for only a minor fraction of the total reservoir of marine dissolved organic carbon, their flux and fate underpins the central role of the ocean in sustaining life on Earth.
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Affiliation(s)
- Mary Ann Moran
- Department of Marine Sciences, University of Georgia, Athens, GA, USA.
| | - Elizabeth B Kujawinski
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA.
| | - William F Schroer
- Department of Marine Sciences, University of Georgia, Athens, GA, USA
| | - Shady A Amin
- Division of Science, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Nicholas R Bates
- Bermuda Institute of Ocean Sciences, St George's, Bermuda.,School of Ocean and Earth Sciences, University of Southampton, Southampton, UK
| | - Erin M Bertrand
- Department of Biology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Rogier Braakman
- Departments of Earth, Atmospheric and Planetary Sciences, and Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - C Titus Brown
- Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, Davis, CA, USA
| | - Markus W Covert
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Scott C Doney
- Department of Environmental Sciences, University of Virginia, Charlottesville, VA, USA
| | - Sonya T Dyhrman
- Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA.,Department of Earth and Environmental Science, Columbia University, Palisades, NY, USA
| | - Arthur S Edison
- Departments of Biochemistry and Genetics, Complex Carbohydrate Research Center, University of Georgia, Athens, GA, USA
| | - A Murat Eren
- Josephine Bay Paul Center, Marine Biological Laboratory, Woods Hole, MA, USA.,Helmholtz-Institute for Functional Marine Biodiversity (HIFMB), University of Oldenburg, Oldenburg, Germany
| | - Naomi M Levine
- Marine and Environmental Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
| | - Liang Li
- Department of Chemistry, University of Alberta, Edmonton, Alberta, Canada
| | - Avena C Ross
- Department of Chemistry, Queen's University, Kingston, Ontario, Canada
| | - Mak A Saito
- Department of Marine Sciences, University of Georgia, Athens, GA, USA
| | - Alyson E Santoro
- Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA, USA
| | - Daniel Segrè
- Department of Biology and Bioinformatics Program, Boston University, Boston, MA, USA
| | - Ashley Shade
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
| | - Matthew B Sullivan
- Departments of Microbiology and Civil, Environmental, and Geodetic Engineering, and Center of Microbiome Science, The Ohio State University, Columbus, OH, USA
| | - Assaf Vardi
- Department of Plant and Environmental Sciences, The Weizmann Institute of Science, Rehovot, Israel
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8
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Bartels B, Svatoš A. Influence of Ion Source Geometry on the Repeatability of Topographically Guided LAESI-MSI. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2022; 33:265-272. [PMID: 35020389 PMCID: PMC8815068 DOI: 10.1021/jasms.1c00262] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 12/07/2021] [Accepted: 12/29/2021] [Indexed: 06/14/2023]
Abstract
Spatially resolving the relative distribution of analyte molecules in biological matter holds great promise in the life sciences. Mass spectrometry imaging (MSI) is a technique that can provide such spatial resolution but remains underused in fields such as chemical ecology, as traditional MSI sample preparation is often chemically or morphologically invasive. Laser ablation electrospray ionization (LAESI)-MSI is a variation of MSI particularly well-suited for situations where chemical sample preparation is too invasive but provides new challenges related to the repeatability of measurement outcomes. We assess the repeatability of LAESI-MSI by sampling a droplet of [ring-13C6]l-phenylalanine with known concentration and expressing the resulting variability as a coefficient of variation, cv. In doing so, we entirely eliminate variability caused by surface morphology or underlying true sample gradients. We determine the limit of detection (LOD) for13C6-Phe by sampling from droplets with successively decreasing but known concentration. We assess the influence of source geometry on the LOD and repeatability by performing these experiments using four distinct variations of sources: one commercial and three custom-built ones. Finally, we extend our study to leaf and stem samples Arabidopsis thaliana and Gossypium hirsutum. We overcome the challenges of LAESI associated with three-dimensional surface morphology by relying on work previously published. Our measurements on both controlled standard and realistic samples give strong evidence that LAESI-MSI's repeatability in current implementations is insufficient for MSI in chemical ecology.
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9
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Brown ER, Moore SG, Gaul DA, Kubanek J. Differentiating toxic and nontoxic congeneric harmful algae using the non-polar metabolome. HARMFUL ALGAE 2021; 110:102129. [PMID: 34887009 DOI: 10.1016/j.hal.2021.102129] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 10/22/2021] [Accepted: 11/01/2021] [Indexed: 06/13/2023]
Abstract
Recognition and rejection of chemically defended prey is critical to maximizing fitness for predators. Paralytic shellfish toxins (PSTs) which strongly inhibit voltage-gated sodium channels in diverse animal taxa are produced by several species of the bloom-forming algal genus Alexandrium where they appear to function as chemical defenses against grazing copepods. Despite PSTs being produced and localized within phytoplankton cells, some copepods distinguish toxic from non-toxic prey, selectively ingesting less toxic cells, in ways that suggest cell surface recognition perhaps associated with non-polar metabolites. In this study LC/MS and NMR-based metabolomics revealed that the non-polar metabolomes of two toxic species (Alexandrium catenella and Alexandrium pacificum) vary considerably from their non-toxic congener Alexandrium tamarense despite all three being very closely related. Toxic and non-toxic Alexandrium spp. were distinguished from each other by metabolites belonging to seven lipid classes. Of these, 17 specific metabolites were significantly more abundant in both toxic A. catenella and A. pacificum compared to non-toxic A. tamarense suggesting that just a small portion of the observed metabolic variability is associated with toxicity. Future experiments aimed at deciphering chemoreception mechanisms of copepod perception of Alexandrium toxicity should consider these metabolites, and the broader lipid classes phosphatidylcholines and sterols, as potential candidate cues.
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Affiliation(s)
- Emily R Brown
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Dr, Atlanta, GA 30332, USA
| | - Sam G Moore
- School of Chemistry and Biochemistry, Georgia Institute of Technology, 901 Atlantic Dr, Atlanta, GA 30332, USA
| | - David A Gaul
- School of Chemistry and Biochemistry, Georgia Institute of Technology, 901 Atlantic Dr, Atlanta, GA 30332, USA
| | - Julia Kubanek
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Dr, Atlanta, GA 30332, USA; School of Chemistry and Biochemistry, Georgia Institute of Technology, 901 Atlantic Dr, Atlanta, GA 30332, USA; Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, 315 Ferst Dr, Atlanta, GA 30332, USA; Center for Microbial Dynamics and Infection, Georgia Institute of Technology, Atlanta, GA 30332, USA.
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10
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The limitless applications of single-cell metabolomics. Curr Opin Biotechnol 2021; 71:115-122. [PMID: 34339935 DOI: 10.1016/j.copbio.2021.07.015] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 07/08/2021] [Accepted: 07/11/2021] [Indexed: 12/28/2022]
Abstract
Single-cell metabolomics (SCM) is currently one of the most powerful tools for performing high-throughput metabolic analysis at the cellular level. The power of single-cell metabolomics to determine the metabolic profiles of individual cells makes it very suitable for decoding cell heterogeneity. SCM bears great potential in cell type identification and differentiation within cell colonies. With the development of various equipment and techniques, SCM analysis has become possible for a wide range of biological samples. Many fields have incorporated this cutting-edge analytic tool to generate fruitful findings. This review article pays close attention to the prevalent techniques utilized in SCM and the exciting new findings and applications developed by studies in phytology, neurology, and oncology using SCM.
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11
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Vallet M, Kaftan F, Grabe V, Ghaderiardakani F, Fenizia S, Svatoš A, Pohnert G, Wichard T. A new glance at the chemosphere of macroalgal-bacterial interactions: In situ profiling of metabolites in symbiosis by mass spectrometry. Beilstein J Org Chem 2021; 17:1313-1322. [PMID: 34136011 PMCID: PMC8182680 DOI: 10.3762/bjoc.17.91] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 04/28/2021] [Indexed: 12/15/2022] Open
Abstract
Symbiosis is a dominant form of life that has been observed numerous times in marine ecosystems. For example, macroalgae coexist with bacteria that produce factors that promote algal growth and morphogenesis. The green macroalga Ulva mutabilis (Chlorophyta) develops into a callus-like phenotype in the absence of its essential bacterial symbionts Roseovarius sp. MS2 and Maribacter sp. MS6. Spatially resolved studies are required to understand symbiont interactions at the microscale level. Therefore, we used mass spectrometry profiling and imaging techniques with high spatial resolution and sensitivity to gain a new perspective on the mutualistic interactions between bacteria and macroalgae. Using atmospheric pressure scanning microprobe matrix-assisted laser desorption/ionisation high-resolution mass spectrometry (AP-SMALDI-HRMS), low-molecular-weight polar compounds were identified by comparative metabolomics in the chemosphere of Ulva. Choline (2-hydroxy-N,N,N-trimethylethan-1-aminium) was only determined in the alga grown under axenic conditions, whereas ectoine (1,4,5,6-tetrahydro-2-methyl-4-pyrimidinecarboxylic acid) was found in bacterial presence. Ectoine was used as a metabolic marker for localisation studies of Roseovarius sp. within the tripartite community because it was produced exclusively by these bacteria. By combining confocal laser scanning microscopy (cLSM) and AP-SMALDI-HRMS, we proved that Roseovarius sp. MS2 settled mainly in the rhizoidal zone (holdfast) of U. mutabilis. Our findings provide the fundament to decipher bacterial symbioses with multicellular hosts in aquatic ecosystems in an ecologically relevant context. As a versatile tool for microbiome research, the combined AP-SMALDI and cLSM imaging analysis with a resolution to level of a single bacterial cell can be easily applied to other microbial consortia and their hosts. The novelty of this contribution is the use of an in situ setup designed to avoid all types of external contamination and interferences while resolving spatial distributions of metabolites and identifying specific symbiotic bacteria.
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Affiliation(s)
- Marine Vallet
- Research Group Phytoplankton Community Interactions, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Filip Kaftan
- Research Group Mass Spectrometry/Proteomics, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Veit Grabe
- Research Group Olfactory Coding, Department of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Fatemeh Ghaderiardakani
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, Germany
| | - Simona Fenizia
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, Germany.,Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Aleš Svatoš
- Research Group Mass Spectrometry/Proteomics, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Georg Pohnert
- Research Group Phytoplankton Community Interactions, Max Planck Institute for Chemical Ecology, Jena, Germany.,Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, Germany.,Microverse Cluster, Friedrich Schiller University Jena, Germany
| | - Thomas Wichard
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, Germany
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12
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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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13
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de Souza LP, Borghi M, Fernie A. Plant Single-Cell Metabolomics-Challenges and Perspectives. Int J Mol Sci 2020; 21:E8987. [PMID: 33256100 PMCID: PMC7730874 DOI: 10.3390/ijms21238987] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 02/07/2023] Open
Abstract
Omics approaches for investigating biological systems were introduced in the mid-1990s and quickly consolidated to become a fundamental pillar of modern biology. The idea of measuring the whole complement of genes, transcripts, proteins, and metabolites has since become widespread and routinely adopted in the pursuit of an infinity of scientific questions. Incremental improvements over technical aspects such as sampling, sensitivity, cost, and throughput pushed even further the boundaries of what these techniques can achieve. In this context, single-cell genomics and transcriptomics quickly became a well-established tool to answer fundamental questions challenging to assess at a whole tissue level. Following a similar trend as the original development of these techniques, proteomics alternatives for single-cell exploration have become more accessible and reliable, whilst metabolomics lag behind the rest. This review summarizes state-of-the-art technologies for spatially resolved metabolomics analysis, as well as the challenges hindering the achievement of sensu stricto metabolome coverage at the single-cell level. Furthermore, we discuss several essential contributions to understanding plant single-cell metabolism, finishing with our opinion on near-future developments and relevant scientific questions that will hopefully be tackled by incorporating these new exciting technologies.
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Affiliation(s)
- Leonardo Perez de Souza
- Max Planck Institute of Molecular Plant Physiology, Am Müehlenberg 1, Golm, 14476 Potsdam, Germany
| | - Monica Borghi
- Department of Biology, Utah State University, 1435 Old Main Hill, Logan, UT 84322, USA;
| | - Alisdair Fernie
- Max Planck Institute of Molecular Plant Physiology, Am Müehlenberg 1, Golm, 14476 Potsdam, Germany
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14
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Kumar G, Shekh A, Jakhu S, Sharma Y, Kapoor R, Sharma TR. Bioengineering of Microalgae: Recent Advances, Perspectives, and Regulatory Challenges for Industrial Application. Front Bioeng Biotechnol 2020; 8:914. [PMID: 33014997 PMCID: PMC7494788 DOI: 10.3389/fbioe.2020.00914] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 07/15/2020] [Indexed: 01/14/2023] Open
Abstract
Microalgae, due to their complex metabolic capacity, are being continuously explored for nutraceuticals, pharmaceuticals, and other industrially important bioactives. However, suboptimal yield and productivity of the bioactive of interest in local and robust wild-type strains are of perennial concerns for their industrial applications. To overcome such limitations, strain improvement through genetic engineering could play a decisive role. Though the advanced tools for genetic engineering have emerged at a greater pace, they still remain underused for microalgae as compared to other microorganisms. Pertaining to this, we reviewed the progress made so far in the development of molecular tools and techniques, and their deployment for microalgae strain improvement through genetic engineering. The recent availability of genome sequences and other omics datasets form diverse microalgae species have remarkable potential to guide strategic momentum in microalgae strain improvement program. This review focuses on the recent and significant improvements in the omics resources, mutant libraries, and high throughput screening methodologies helpful to augment research in the model and non-model microalgae. Authors have also summarized the case studies on genetically engineered microalgae and highlight the opportunities and challenges that are emerging from the current progress in the application of genome-editing to facilitate microalgal strain improvement. Toward the end, the regulatory and biosafety issues in the use of genetically engineered microalgae in commercial applications are described.
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Affiliation(s)
- Gulshan Kumar
- Agricultural Biotechnology Division, National Agri-Food Biotechnology Institute (NABI), Sahibzada Ajit Singh Nagar, India
| | - Ajam Shekh
- Plant Cell Biotechnology Department, CSIR-Central Food Technological Research Institute (CFTRI), Mysuru, India
| | - Sunaina Jakhu
- Agricultural Biotechnology Division, National Agri-Food Biotechnology Institute (NABI), Sahibzada Ajit Singh Nagar, India
| | - Yogesh Sharma
- Agricultural Biotechnology Division, National Agri-Food Biotechnology Institute (NABI), Sahibzada Ajit Singh Nagar, India
| | - Ritu Kapoor
- Agricultural Biotechnology Division, National Agri-Food Biotechnology Institute (NABI), Sahibzada Ajit Singh Nagar, India
| | - Tilak Raj Sharma
- Division of Crop Science, Indian Council of Agricultural Research, New Delhi, India
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Kumar R, Ghosh M, Kumar S, Prasad M. Single Cell Metabolomics: A Future Tool to Unmask Cellular Heterogeneity and Virus-Host Interaction in Context of Emerging Viral Diseases. Front Microbiol 2020; 11:1152. [PMID: 32582094 PMCID: PMC7286130 DOI: 10.3389/fmicb.2020.01152] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 05/06/2020] [Indexed: 12/15/2022] Open
Abstract
Viral emergence is an unpredictable but obvious event, particularly in the era of climate change and globalization. Efficient management of viral outbreaks depends on pre-existing knowledge and alertness. The potential hotspots of viral emergence often remain neglected and the information related to them is insufficient, particularly for emerging viruses. Viral replication and transmission rely upon usurping the host metabolic machineries. So altered host metabolic pathways can be exploited for containment of these viruses. Metabolomics provides the insight for tracing out such checkpoints. Consequently introspection of metabolic alteration at virus-host interface has evolved as prime area in current virology research. Chromatographic separation followed by mass spectrometry has been used as the predominant analytical platform in bulk of the analyses followed by nuclear magnetic resonance (NMR) and fluorescence based techniques. Although valuable information regarding viral replication and modulation of host metabolic pathways have been extracted but ambiguity often superseded the real events due to population effect over the infected cells. Exploration of cellular heterogeneity and differentiation of infected cells from the nearby healthy ones has become essential. Single cell metabolomics (SCM) emerges as necessity to explore such minute details. Mass spectrometry imaging (MSI) coupled with several soft ionization techniques such as electrospray ionization (ESI), laser ablation electrospray ionization (LAESI), matrix assisted laser desorption/ionization (MALDI), matrix-free laser desorption ionization (LDI) have evolved as the best suited platforms for SCM analyses. The potential of SCM has already been exploited to resolve several biological conundrums. Thus SCM is knocking at the door of virus-host interface.
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Affiliation(s)
- Rajesh Kumar
- Department of Veterinary Physiology and Biochemistry, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar, India
| | - Mayukh Ghosh
- Department of Veterinary Physiology and Biochemistry, RGSC, Banaras Hindu University, Mirzapur, India
| | - Sandeep Kumar
- Department of Veterinary Surgery and Radiology, College of Veterinary Sciences, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar, India
| | - Minakshi Prasad
- Department of Animal Biotechnology, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar, India
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Subcellular Chemical Imaging: New Avenues in Cell Biology. Trends Cell Biol 2020; 30:173-188. [DOI: 10.1016/j.tcb.2019.12.007] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Revised: 12/10/2019] [Accepted: 12/17/2019] [Indexed: 12/31/2022]
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Baumeister TUH, Vallet M, Kaftan F, Guillou L, Svatoš A, Pohnert G. Identification to species level of live single microalgal cells from plankton samples with matrix-free laser/desorption ionization mass spectrometry. Metabolomics 2020; 16:28. [PMID: 32090296 PMCID: PMC7036359 DOI: 10.1007/s11306-020-1646-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 01/27/2020] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Marine planktonic communities are complex microbial consortia often dominated by microscopic algae. The taxonomic identification of individual phytoplankton cells usually relies on their morphology and demands expert knowledge. Recently, a live single-cell mass spectrometry (LSC-MS) pipeline was developed to generate metabolic profiles of microalgae. OBJECTIVE Taxonomic identification of diverse microalgal single cells from collection strains and plankton samples based on the metabolic fingerprints analyzed with matrix-free laser desorption/ionization high-resolution mass spectrometry. METHODS Matrix-free atmospheric pressure laser-desorption ionization mass spectrometry was performed to acquire single-cell mass spectra from collection strains and prior identified environmental isolates. The computational identification of microalgal species was performed by spectral pattern matching (SPM). Three similarity scores and a bootstrap-derived confidence score were evaluated in terms of their classification performance. The effects of high and low-mass resolutions on the classification success were evaluated. RESULTS Several hundred single-cell mass spectra from nine genera and nine species of marine microalgae were obtained. SPM enabled the identification of single cells at the genus and species level with high accuracies. The receiver operating characteristic (ROC) curves indicated a good performance of the similarity measures but were outperformed by the bootstrap-derived confidence scores. CONCLUSION This is the first study to solve taxonomic identification of microalgae based on the metabolic fingerprints of the individual cell using an SPM approach.
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Affiliation(s)
- Tim U H Baumeister
- Max Planck Institute for Chemical Ecology, Max Planck Fellow Group On Plankton Community Interaction, Hans-Knöll-Str. 8, 07745, Jena, Germany
| | - Marine Vallet
- Max Planck Institute for Chemical Ecology, Max Planck Fellow Group On Plankton Community Interaction, Hans-Knöll-Str. 8, 07745, Jena, Germany
| | - Filip Kaftan
- Research Group Mass Spectrometry/Proteomics, Max Planck Institute for Chemical Ecology, Hans-Knöll-Str. 8, 07745, Jena, Germany
| | - Laure Guillou
- Sorbonne Université, CNRS, UMR7144 Adaptation Et Diversité en Milieu Marin, Ecology of Marine Plankton (ECOMAP), Station Biologique de Roscoff SBR, 29680, Roscoff, France
| | - Aleš Svatoš
- Research Group Mass Spectrometry/Proteomics, Max Planck Institute for Chemical Ecology, Hans-Knöll-Str. 8, 07745, Jena, Germany.
| | - Georg Pohnert
- Max Planck Institute for Chemical Ecology, Max Planck Fellow Group On Plankton Community Interaction, Hans-Knöll-Str. 8, 07745, Jena, Germany.
- Department of Bioorganic Analytics, Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University Jena, Lessingstr. 8, 07743, Jena, Germany.
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Vallet M, Baumeister TUH, Kaftan F, Grabe V, Buaya A, Thines M, Svatoš A, Pohnert G. The oomycete Lagenisma coscinodisci hijacks host alkaloid synthesis during infection of a marine diatom. Nat Commun 2019; 10:4938. [PMID: 31666506 PMCID: PMC6821873 DOI: 10.1038/s41467-019-12908-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 10/03/2019] [Indexed: 01/01/2023] Open
Abstract
Flagellated oomycetes frequently infect unicellular algae, thus limiting their proliferation. Here we show that the marine oomycete Lagenisma coscinodisci rewires the metabolome of the bloom-forming diatom Coscinodiscus granii, thereby promoting infection success. The algal alkaloids β-carboline and 4-carboxy-2,3,4,9-tetrahydro-1H-β-carboline are induced during infection. Single-cell profiling with AP-MALDI-MS and confocal laser scanning microscopy reveals that algal carbolines accumulate in the reproductive form of the parasite. The compounds arrest the algal cell division, increase the infection rate and induce plasmolysis in the host. Our results indicate that the oomycete manipulates the host metabolome to support its own multiplication. Flagellated oomycetes frequently infect unicellular algae, thus limiting their proliferation. Here, the authors show that an oomycete rewires the metabolome of a marine bloom-forming diatom, thereby promoting infection success.
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Affiliation(s)
- Marine Vallet
- Research Group Plankton Community Interaction, Max Planck Institute for Chemical Ecology, Jena, Germany.
| | - Tim U H Baumeister
- Research Group Plankton Community Interaction, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Filip Kaftan
- Research Group Mass Spectrometry/Proteomics, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Veit Grabe
- Research Group Olfactory Coding, Department of Evolutionary Neuroethology, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Anthony Buaya
- Senckenberg Biodiversity and Climate Research Centre, Frankfurt am Main, Germany
| | - Marco Thines
- Senckenberg Biodiversity and Climate Research Centre, Frankfurt am Main, Germany.,Department of Biological Sciences, Institute for Ecology, Evolution and Diversity, Goethe University, Frankfurt am Main, Germany
| | - Aleš Svatoš
- Research Group Mass Spectrometry/Proteomics, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Georg Pohnert
- Research Group Plankton Community Interaction, Max Planck Institute for Chemical Ecology, Jena, Germany. .,Bioorganic Analytics, Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University, Jena, Germany. .,Microverse Cluster, Friedrich Schiller University Jena, Neugasse 23, 07743, Jena, Germany.
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Kumar A, Misra BB. Challenges and Opportunities in Cancer Metabolomics. Proteomics 2019; 19:e1900042. [PMID: 30950571 DOI: 10.1002/pmic.201900042] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 03/22/2019] [Indexed: 12/23/2022]
Abstract
Challenges in metabolomics for a given spectrum of disease are more or less comparable, ranging from the accurate measurement of metabolite abundance, compound annotation, identification of unknown constituents, and interpretation of untargeted and analysis of high throughput targeted metabolomics data leading to the identification of biomarkers. However, metabolomics approaches in cancer studies specifically suffer from several additional challenges and require robust ways to sample the cells and tissues in order to tackle the constantly evolving cancer landscape. These constraints include, but are not limited to, discriminating the signals from given cell types and those that are cancer specific, discerning signals that are systemic and confounded, cell culture-based challenges associated with cell line identities and media standardizations, the need to look beyond Warburg effects, citrate cycle, lactate metabolism, and identifying and developing technologies to precisely and effectively sample and profile the heterogeneous tumor environment. This review article discusses some of the current and pertinent hurdles in cancer metabolomics studies. In addition, it addresses some of the most recent and exciting developments in metabolomics that may address some of these issues. The aim of this article is to update the oncometabolomics research community about the challenges and potential solutions to these issues.
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Affiliation(s)
- Ashish Kumar
- Department of Genetics, Texas Biomedical Research Institute, 7620 NW Loop 410, San Antonio, TX, 78227, USA
| | - Biswapriya B Misra
- Center for Precision Medicine, Department of Internal Medicine, Section on Molecular Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA
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