1
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McKinnon JC, Balez R, Young RSE, Brown ML, Lum JS, Robinson L, Belov ME, Ooi L, Tortorella S, Mitchell TW, Ellis SR. MALDI-2-Enabled Oversampling for the Mass Spectrometry Imaging of Metabolites at Single-Cell Resolution. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024. [PMID: 39137242 DOI: 10.1021/jasms.4c00241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Abstract
Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can provide valuable insights into the metabolome of complex biological systems such as organ tissues and cells. However, obtaining metabolite data at single-cell spatial resolutions presents a few technological challenges. Generally, spatial resolution is defined by the increment the sample stage moves between laser ablation spots. Stage movements less than the diameter of the focused laser beam (i.e., oversampling) can improve spatial resolution; however, such oversampling conditions result in a reduction in sensitivity. To overcome this, we combine an oversampling approach with laser postionization (MALDI-2), which allows for both higher spatial resolution and improved analyte ionization efficiencies. This approach provides significant enhancements to sensitivity for various metabolite classes (e.g., amino acids, purines, carbohydrates etc.), with mass spectral intensities from 6 to 8 μm pixel sizes (from a laser spot size of ∼13 μm) being commensurate with or higher than those obtained by conventional MALDI at 20 μm pixel sizes for many different metabolites. This technique has been used to map the distribution of metabolites throughout mouse spinal cord tissue to observe how metabolite localizations change throughout specific anatomical regions, such as those distributed to the somatosensory area of the dorsal horn, white matter, gray matter, and ventral horn. Furthermore, this method is utilized for single-cell metabolomics of human iPSC-derived astrocytes at 10 μm pixel sizes whereby many different metabolites, including nucleotides, were detected from individual cells while providing insight into cellular localizations.
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Affiliation(s)
- Jayden C McKinnon
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
| | - Rachelle Balez
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
| | - Reuben S E Young
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
| | - Mikayla L Brown
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
| | - Jeremy S Lum
- Molecular Horizons, School of Medical, Indigenous and Health Science, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
| | - Liam Robinson
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
| | - Mikhail E Belov
- Spectroglyph LLC, Kennewick, Washington 99338, United States
| | - Lezanne Ooi
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
| | - Sara Tortorella
- Molecular Horizon srl, Via Montelino 30, Bettona, PG 06084, Italy
| | - Todd W Mitchell
- Molecular Horizons, School of Medical, Indigenous and Health Science, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
| | - Shane R Ellis
- Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
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2
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Lane AN, Higashi RM, Fan TWM. Challenges of Spatially Resolved Metabolism in Cancer Research. Metabolites 2024; 14:383. [PMID: 39057706 PMCID: PMC11278851 DOI: 10.3390/metabo14070383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Revised: 06/28/2024] [Accepted: 07/07/2024] [Indexed: 07/28/2024] Open
Abstract
Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing the basis for flux analysis. As the diversity of stable isotope-enriched compounds is very high, and with newer approaches to multiplexing, the coverage of metabolism is now very extensive. However, as the complexity of the model increases, including more kinds of interacting cell types and interorgan communication, the analytical complexity also increases. Further, as studies move further into spatially resolved biology, new technical problems have to be overcome owing to the small number of analytes present in the confines of a single cell or cell compartment. Here, we review the overall goals and solutions made possible by stable isotope tracing and their applications to models of increasing complexity. Finally, we discuss progress and outstanding difficulties in high-resolution spatially resolved tracer-based metabolic studies.
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Affiliation(s)
- Andrew N. Lane
- Department of Toxicology and Cancer Biology and Markey Cancer Center, University of Kentucky, 789 S. Limestone St., Lexington, KY 40536, USA; (R.M.H.); (T.W.-M.F.)
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3
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Verheijen FWM, Tran TNM, Chang J, Broere F, Zaal EA, Berkers CR. Deciphering metabolic crosstalk in context: lessons from inflammatory diseases. Mol Oncol 2024; 18:1759-1776. [PMID: 38275212 PMCID: PMC11223610 DOI: 10.1002/1878-0261.13588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 11/02/2023] [Accepted: 01/15/2024] [Indexed: 01/27/2024] Open
Abstract
Metabolism plays a crucial role in regulating the function of immune cells in both health and disease, with altered metabolism contributing to the pathogenesis of cancer and many inflammatory diseases. The local microenvironment has a profound impact on the metabolism of immune cells. Therefore, immunological and metabolic heterogeneity as well as the spatial organization of cells in tissues should be taken into account when studying immunometabolism. Here, we highlight challenges of investigating metabolic communication. Additionally, we review the capabilities and limitations of current technologies for studying metabolism in inflamed microenvironments, including single-cell omics techniques, flow cytometry-based methods (Met-Flow, single-cell energetic metabolism by profiling translation inhibition (SCENITH)), cytometry by time of flight (CyTOF), cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), and mass spectrometry imaging. Considering the importance of metabolism in regulating immune cells in diseased states, we also discuss the applications of metabolomics in clinical research, as well as some hurdles to overcome to implement these techniques in standard clinical practice. Finally, we provide a flowchart to assist scientists in designing effective strategies to unravel immunometabolism in disease-relevant contexts.
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Affiliation(s)
- Fenne W. M. Verheijen
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
- Division of Infectious Diseases and Immunology, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
| | - Thi N. M. Tran
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular ResearchUtrecht UniversityThe Netherlands
| | - Jung‐Chin Chang
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
| | - Femke Broere
- Division of Infectious Diseases and Immunology, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
| | - Esther A. Zaal
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
| | - Celia R. Berkers
- Division of Cell Biology, Metabolism & Cancer, Department Biomolecular Health Sciences, Faculty of Veterinary MedicineUtrecht UniversityThe Netherlands
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4
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Zhou J, Chng WJ. Unveiling novel insights in acute myeloid leukemia through single-cell RNA sequencing. Front Oncol 2024; 14:1365330. [PMID: 38711849 PMCID: PMC11070491 DOI: 10.3389/fonc.2024.1365330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 04/09/2024] [Indexed: 05/08/2024] Open
Abstract
Acute myeloid leukemia (AML) is a complex and heterogeneous group of aggressive hematopoietic stem cell disease. The presence of diverse and functionally distinct populations of leukemia cells within the same patient's bone marrow or blood poses a significant challenge in diagnosing and treating AML. A substantial proportion of AML patients demonstrate resistance to induction chemotherapy and a grim prognosis upon relapse. The rapid advance in next generation sequencing technologies, such as single-cell RNA-sequencing (scRNA-seq), has revolutionized our understanding of AML pathogenesis by enabling high-resolution interrogation of the cellular heterogeneity in the AML ecosystem, and their transcriptional signatures at a single-cell level. New studies have successfully characterized the inextricably intertwined interactions among AML cells, immune cells and bone marrow microenvironment and their contributions to the AML development, therapeutic resistance and relapse. These findings have deepened and broadened our understanding the complexity and heterogeneity of AML, which are difficult to detect with bulk RNA-seq. This review encapsulates the burgeoning body of knowledge generated through scRNA-seq, providing the novel insights and discoveries it has unveiled in AML biology. Furthermore, we discuss the potential implications of scRNA-seq in therapeutic opportunities, focusing on immunotherapy. Finally, we highlight the current limitations and future direction of scRNA-seq in the field.
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Affiliation(s)
- Jianbiao Zhou
- Cancer Science Institute of Singapore, Center for Translational Medicine, National University of Singapore, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- NUS Center for Cancer Research, Center for Translational Medicine, Singapore, Singapore
| | - Wee-Joo Chng
- Cancer Science Institute of Singapore, Center for Translational Medicine, National University of Singapore, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- NUS Center for Cancer Research, Center for Translational Medicine, Singapore, Singapore
- Department of Hematology-Oncology, National University Cancer Institute of Singapore (NCIS), The National University Health System (NUHS), Singapore, Singapore
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5
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Brennan PG, Mota L, Aridi T, Patel N, Liang P, Ferran C. Advancements in Omics and Breakthrough Gene Therapies: A Glimpse into the Future of Peripheral Artery Disease. Ann Vasc Surg 2024:S0890-5096(24)00156-0. [PMID: 38582204 DOI: 10.1016/j.avsg.2024.01.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 01/01/2024] [Indexed: 04/08/2024]
Abstract
Peripheral artery disease (PAD), a highly prevalent global disease, associates with significant morbidity and mortality in affected patients. Despite progress in endovascular and open revascularization techniques for advanced PAD, these interventions grapple with elevated rates of arterial restenosis and vein graft failure attributed to intimal hyperplasia (IH). Novel multiomics technologies, coupled with sophisticated analyses tools recently powered by advances in artificial intelligence, have enabled the study of atherosclerosis and IH with unprecedented single-cell and spatial precision. Numerous studies have pinpointed gene hubs regulating pivotal atherogenic and atheroprotective signaling pathways as potential therapeutic candidates. Leveraging advancements in viral and nonviral gene therapy (GT) platforms, gene editing technologies, and cutting-edge biomaterial reservoirs for delivery uniquely positions us to develop safe, efficient, and targeted GTs for PAD-related diseases. Gene therapies appear particularly fitting for ex vivo genetic engineering of IH-resistant vein grafts. This manuscript highlights currently available state-of-the-art multiomics approaches, explores promising GT-based candidates, and details GT delivery modalities employed by our laboratory and others to thwart mid-term vein graft failure caused by IH, as well as other PAD-related conditions. The potential clinical translation of these targeted GTs holds the promise to revolutionize PAD treatment, thereby enhancing patients' quality of life and life expectancy.
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Affiliation(s)
- Phillip G Brennan
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Lucas Mota
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Tarek Aridi
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Nyah Patel
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Patric Liang
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Christiane Ferran
- Division of Vascular and Endovascular Surgery, and Center for Vascular Biology Research, Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; Division of Nephrology and the Transplant Institute, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA.
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6
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Ewald S, Nasuhidehnavi A, Feng TY, Lesani M, McCall LI. The intersection of host in vivo metabolism and immune responses to infection with kinetoplastid and apicomplexan parasites. Microbiol Mol Biol Rev 2024; 88:e0016422. [PMID: 38299836 PMCID: PMC10966954 DOI: 10.1128/mmbr.00164-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024] Open
Abstract
SUMMARYProtozoan parasite infection dramatically alters host metabolism, driven by immunological demand and parasite manipulation strategies. Immunometabolic checkpoints are often exploited by kinetoplastid and protozoan parasites to establish chronic infection, which can significantly impair host metabolic homeostasis. The recent growth of tools to analyze metabolism is expanding our understanding of these questions. Here, we review and contrast host metabolic alterations that occur in vivo during infection with Leishmania, trypanosomes, Toxoplasma, Plasmodium, and Cryptosporidium. Although genetically divergent, there are commonalities among these pathogens in terms of metabolic needs, induction of the type I immune responses required for clearance, and the potential for sustained host metabolic dysbiosis. Comparing these pathogens provides an opportunity to explore how transmission strategy, nutritional demand, and host cell and tissue tropism drive similarities and unique aspects in host response and infection outcome and to design new strategies to treat disease.
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Affiliation(s)
- Sarah Ewald
- Department of Microbiology, Immunology, and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Azadeh Nasuhidehnavi
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, USA
| | - Tzu-Yu Feng
- Department of Microbiology, Immunology, and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Mahbobeh Lesani
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA
| | - Laura-Isobel McCall
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, USA
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, Oklahoma, USA
- Department of Chemistry and Biochemistry, San Diego State University, San Diego, California, USA
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7
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Hu L, De Hoyos D, Lei Y, West AP, Walsh AJ. 3D convolutional neural networks predict cellular metabolic pathway use from fluorescence lifetime decay data. APL Bioeng 2024; 8:016112. [PMID: 38420625 PMCID: PMC10901549 DOI: 10.1063/5.0188476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 01/30/2024] [Indexed: 03/02/2024] Open
Abstract
Fluorescence lifetime imaging of the co-enzyme reduced nicotinamide adenine dinucleotide (NADH) offers a label-free approach for detecting cellular metabolic perturbations. However, the relationships between variations in NADH lifetime and metabolic pathway changes are complex, preventing robust interpretation of NADH lifetime data relative to metabolic phenotypes. Here, a three-dimensional convolutional neural network (3D CNN) trained at the cell level with 3D NAD(P)H lifetime decay images (two spatial dimensions and one time dimension) was developed to identify metabolic pathway usage by cancer cells. NADH fluorescence lifetime images of MCF7 breast cancer cells with three isolated metabolic pathways, glycolysis, oxidative phosphorylation, and glutaminolysis were obtained by a multiphoton fluorescence lifetime microscope and then segmented into individual cells as the input data for the classification models. The 3D CNN models achieved over 90% accuracy in identifying cancer cells reliant on glycolysis, oxidative phosphorylation, or glutaminolysis. Furthermore, the model trained with human breast cancer cell data successfully predicted the differences in metabolic phenotypes of macrophages from control and POLG-mutated mice. These results suggest that the integration of autofluorescence lifetime imaging with 3D CNNs enables intracellular spatial patterns of NADH intensity and temporal dynamics of the lifetime decay to discriminate multiple metabolic phenotypes. Furthermore, the use of 3D CNNs to identify metabolic phenotypes from NADH fluorescence lifetime decay images eliminates the need for time- and expertise-demanding exponential decay fitting procedures. In summary, metabolic-prediction CNNs will enable live-cell and in vivo metabolic measurements with single-cell resolution, filling a current gap in metabolic measurement technologies.
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Affiliation(s)
- Linghao Hu
- Department of Biomedical Engineering, Texas A&M University, College Station, Texas 77843, USA
| | - Daniela De Hoyos
- Department of Biomedical Engineering, Texas A&M University, College Station, Texas 77843, USA
| | - Yuanjiu Lei
- Department of Microbial Pathogenesis and Immunology, School of Medicine, Texas A&M University, Bryan, Texas 77807, USA
| | | | - Alex J. Walsh
- Department of Biomedical Engineering, Texas A&M University, College Station, Texas 77843, USA
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8
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Kwakye-Nuako G, Middleton CE, McCall LI. Small molecule mediators of host-T. cruzi-environment interactions in Chagas disease. PLoS Pathog 2024; 20:e1012012. [PMID: 38457443 PMCID: PMC10923493 DOI: 10.1371/journal.ppat.1012012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/10/2024] Open
Abstract
Small molecules (less than 1,500 Da) include major biological signals that mediate host-pathogen-microbiome communication. They also include key intermediates of metabolism and critical cellular building blocks. Pathogens present with unique nutritional needs that restrict pathogen colonization or promote tissue damage. In parallel, parts of host metabolism are responsive to immune signaling and regulated by immune cascades. These interactions can trigger both adaptive and maladaptive metabolic changes in the host, with microbiome-derived signals also contributing to disease progression. In turn, targeting pathogen metabolic needs or maladaptive host metabolic changes is an important strategy to develop new treatments for infectious diseases. Trypanosoma cruzi is a single-celled eukaryotic pathogen and the causative agent of Chagas disease, a neglected tropical disease associated with cardiac and intestinal dysfunction. Here, we discuss the role of small molecules during T. cruzi infection in its vector and in the mammalian host. We integrate these findings to build a theoretical interpretation of how maladaptive metabolic changes drive Chagas disease and extrapolate on how these findings can guide drug development.
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Affiliation(s)
- Godwin Kwakye-Nuako
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, United States of America
- Department of Biomedical Sciences, School of Allied Health Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, Ghana
| | - Caitlyn E. Middleton
- Department of Chemistry and Biochemistry, San Diego State University, San Diego, California, United States of America
| | - Laura-Isobel McCall
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma, United States of America
- Department of Chemistry and Biochemistry, San Diego State University, San Diego, California, United States of America
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9
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Wevers D, Ramautar R, Clark C, Hankemeier T, Ali A. Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics. Electrophoresis 2023; 44:2000-2024. [PMID: 37667867 DOI: 10.1002/elps.202300105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 08/08/2023] [Accepted: 08/19/2023] [Indexed: 09/06/2023]
Abstract
Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.
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Affiliation(s)
- Dirk Wevers
- Wageningen University and Research, Wageningen, The Netherlands
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Rawi Ramautar
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Charlie Clark
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Thomas Hankemeier
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Ahmed Ali
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
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10
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Pandian K, Matsui M, Hankemeier T, Ali A, Okubo-Kurihara E. Advances in single-cell metabolomics to unravel cellular heterogeneity in plant biology. PLANT PHYSIOLOGY 2023; 193:949-965. [PMID: 37338502 PMCID: PMC10517197 DOI: 10.1093/plphys/kiad357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/03/2023] [Accepted: 05/17/2023] [Indexed: 06/21/2023]
Abstract
Single-cell metabolomics is a powerful tool that can reveal cellular heterogeneity and can elucidate the mechanisms of biological phenomena in detail. It is a promising approach in studying plants, especially when cellular heterogeneity has an impact on different biological processes. In addition, metabolomics, which can be regarded as a detailed phenotypic analysis, is expected to answer previously unrequited questions which will lead to expansion of crop production, increased understanding of resistance to diseases, and in other applications as well. In this review, we will introduce the flow of sample acquisition and single-cell techniques to facilitate the adoption of single-cell metabolomics. Furthermore, the applications of single-cell metabolomics will be summarized and reviewed.
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Affiliation(s)
- Kanchana Pandian
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Einstein Road 55, 2333 CC Leiden, The Netherlands
| | - Minami Matsui
- RIKEN, Center for Sustainable Resource Science, Kanagawa 230-0045, Japan
| | - Thomas Hankemeier
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Einstein Road 55, 2333 CC Leiden, The Netherlands
| | - Ahmed Ali
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Einstein Road 55, 2333 CC Leiden, The Netherlands
| | - Emiko Okubo-Kurihara
- RIKEN, Center for Sustainable Resource Science, Kanagawa 230-0045, Japan
- College of Science, Rikkyo University, Tokyo 171-8501, Japan
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11
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Zhang C, Le Dévédec SE, Ali A, Hankemeier T. Single-cell metabolomics by mass spectrometry: ready for primetime? Curr Opin Biotechnol 2023; 82:102963. [PMID: 37356380 DOI: 10.1016/j.copbio.2023.102963] [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: 02/08/2023] [Revised: 04/17/2023] [Accepted: 05/23/2023] [Indexed: 06/27/2023]
Abstract
Single-cell metabolomics (SCMs) is a powerful tool for studying cellular heterogeneity by providing insight into the differences between individual cells. With the development of a set of promising SCMs pipelines, this maturing technology is expected to be widely used in biomedical research. However, before SCMs is ready for primetime, there are some challenges to overcome. In this review, we summarize the trends and challenges in the development of SCMs. We also highlight the latest methodologies, applications, and sketch the perspective for integration with other omics and imaging approaches.
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Affiliation(s)
- Congrou Zhang
- Metabolomics and Analytics Center, Leiden Academic Centre of Drug Research, Leiden University, Leiden, the Netherlands
| | - Sylvia E Le Dévédec
- Division of Drug Discovery and Safety, Leiden Academic Centre of Drug Research, Leiden University, Leiden, the Netherlands
| | - Ahmed Ali
- Metabolomics and Analytics Center, Leiden Academic Centre of Drug Research, Leiden University, Leiden, the Netherlands.
| | - Thomas Hankemeier
- Metabolomics and Analytics Center, Leiden Academic Centre of Drug Research, Leiden University, Leiden, the Netherlands.
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12
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Aharoni A, Goodacre R, Fernie AR. Plant and microbial sciences as key drivers in the development of metabolomics research. Proc Natl Acad Sci U S A 2023; 120:e2217383120. [PMID: 36930598 PMCID: PMC10041103 DOI: 10.1073/pnas.2217383120] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
Abstract
This year marks the 25th anniversary of the coinage of the term metabolome [S. G. Oliver et al., Trends Biotech. 16, 373-378 (1998)]. As the field rapidly advances, it is important to take stock of the progress which has been made to best inform the disciplines future. While a medical-centric perspective on metabolomics has recently been published [M. Giera et al., Cell Metab. 34, 21-34 (2022)], this largely ignores the pioneering contributions made by the plant and microbial science communities. In this perspective, we provide a contemporary overview of all fields in which metabolomics is employed with particular emphasis on both methodological and application breakthroughs made in plant and microbial sciences that have shaped this evolving research discipline from the very early days of its establishment. This will not cover all types of metabolomics assays currently employed but will focus mainly on those utilizing mass spectrometry-based measurements since they are currently by far the most prominent. Having established the historical context of metabolomics, we will address the key challenges currently facing metabolomics and offer potential approaches by which these can be faced. Most salient among these is the fact that the vast majority of mass features are as yet not annotated with high confidence; what we may refer to as definitive identification. We discuss the potential of both standard compound libraries and artificial intelligence technologies to address this challenge and the use of natural variance-based approaches such as genome-wide association studies in attempt to assign specific functions to the myriad of structurally similar and complex specialized metabolites. We conclude by stating our contention that as these challenges are epic and that they will need far greater cooperative efforts from biologists, chemists, and computer scientists with an interest in all kingdoms of life than have been made to date. Ultimately, a better linkage of metabolome and genome data will likely also be needed particularly considering the Earth BioGenome Project.
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Affiliation(s)
- Asaph Aharoni
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot76100, Israel
| | - Royston Goodacre
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, LiverpoolL69 7BE, UK
| | - Alisdair R. Fernie
- Max-Planck-Institute for Molecular Plant Physiology, Potsdam14476, Germany
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13
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Andrade de Oliveira K, Sengupta S, Yadav AK, Clarke R. The complex nature of heterogeneity and its roles in breast cancer biology and therapeutic responsiveness. Front Endocrinol (Lausanne) 2023; 14:1083048. [PMID: 36909339 PMCID: PMC9997040 DOI: 10.3389/fendo.2023.1083048] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 02/02/2023] [Indexed: 02/25/2023] Open
Abstract
Heterogeneity is a complex feature of cells and tissues with many interacting components. Depending on the nature of the research context, interacting features of cellular, drug response, genetic, molecular, spatial, temporal, and vascular heterogeneity may be present. We describe the various forms of heterogeneity with examples of their interactions and how they play a role in affecting cellular phenotype and drug responses in breast cancer. While cellular heterogeneity may be the most widely described and invoked, many forms of heterogeneity are evident within the tumor microenvironment and affect responses to the endocrine and cytotoxic drugs widely used in standard clinical care. Drug response heterogeneity is a critical determinant of clinical response and curative potential and also is multifaceted when encountered. The interactive nature of some forms of heterogeneity is readily apparent. For example, the process of metastasis has the properties of both temporal and spatial heterogeneity within the host, whereas each individual metastatic deposit may exhibit cellular, genetic, molecular, and vascular heterogeneity. This review describes the many forms of heterogeneity, their integrated activities, and offers some insights into how heterogeneity may be understood and studied in the future.
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Affiliation(s)
- Karla Andrade de Oliveira
- The Hormel Institute, University of Minnesota, Austin, MN, United States
- Department of Biochemistry and Pharmacology, Universidade Federal do Piaui, Piauí, Brazil
| | - Surojeet Sengupta
- The Hormel Institute, University of Minnesota, Austin, MN, United States
| | - Anil Kumar Yadav
- The Hormel Institute, University of Minnesota, Austin, MN, United States
| | - Robert Clarke
- The Hormel Institute, University of Minnesota, Austin, MN, United States
- *Correspondence: Robert Clarke,
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May JC, McLean JA. Integrating ion mobility into comprehensive multidimensional metabolomics workflows: critical considerations. Metabolomics 2022; 18:104. [PMID: 36472678 DOI: 10.1007/s11306-022-01961-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 11/18/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Ion mobility (IM) separation capabilities are now widely available to researchers through several commercial vendors and are now being adopted into many metabolomics workflows. The added peak capacity that ion mobility offers with minimal compromise to other analytical figures-of-merit has provided real benefits to sensitivity and structural selectivity and have allowed more specific metabolite annotations to be assigned in untargeted workflows. One of the greatest promises of contemporary IM-enabled instrumentation is the capability of operating multiple analytical dimensions inline with minimal sample volumes, which has the potential to address many grand challenges currently faced in the omics fields. However, comprehensive operation of multidimensional mass spectrometry comes with its own inherent challenges that, beyond operational complexity, may not be immediately obvious to practitioners of these techniques. AIM OF REVIEW In this review, we outline the strengths and considerations for incorporating IM analysis in metabolomics workflows and provide a critical but forward-looking perspective on the contemporary challenges and prospects associated with interpreting IM data into chemical knowledge. KEY SCIENTIFIC CONCEPTS OF REVIEW We outline a strategy for unifying IM-derived collision cross section (CCS) measurements obtained from different IM techniques and discuss the emerging field of high resolution ion mobility (HRIM) that is poised to address many of the contemporary challenges associated with ion mobility metabolomics. Whereas the LC step limits the throughput of comprehensive LC-IM-MS, the higher peak capacity of HRIM can allow fast LC gradients or rapid sample cleanup via solid-phase extraction (SPE) to be utilized, significantly improving the sample throughput.
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Affiliation(s)
- Jody C May
- Center for Innovative Technology, Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - John A McLean
- Center for Innovative Technology, Department of Chemistry, Vanderbilt University, Nashville, TN, USA.
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