1
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Wang X, Peng R, Zhao L. Multiscale metabolomics techniques: Insights into neuroscience research. Neurobiol Dis 2024; 198:106541. [PMID: 38806132 DOI: 10.1016/j.nbd.2024.106541] [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: 04/10/2024] [Revised: 05/21/2024] [Accepted: 05/23/2024] [Indexed: 05/30/2024] Open
Abstract
The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.
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Affiliation(s)
- Xiaoya Wang
- Beijing Institute of Radiation Medicine, Beijing 100850, China
| | - Ruiyun Peng
- Beijing Institute of Radiation Medicine, Beijing 100850, China.
| | - Li Zhao
- Beijing Institute of Radiation Medicine, Beijing 100850, China.
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2
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Cui N, Xu X, Zhou F. Single-cell technologies in psoriasis. Clin Immunol 2024; 264:110242. [PMID: 38750947 DOI: 10.1016/j.clim.2024.110242] [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: 09/25/2023] [Revised: 03/30/2024] [Accepted: 05/01/2024] [Indexed: 05/24/2024]
Abstract
Psoriasis is a chronic and recurrent inflammatory skin disorder. The primary manifestation of psoriasis arises from disturbances in the cutaneous immune microenvironment, but the specific functions of the cellular components within this microenvironment remain unknown. Recent advancements in single-cell technologies have enabled the detection of multi-omics at the level of individual cells, including single-cell transcriptome, proteome, and metabolome, which have been successfully applied in studying autoimmune diseases, and other pathologies. These techniques allow the identification of heterogeneous cell clusters and their varying contributions to disease development. Considering the immunological traits of psoriasis, an in-depth exploration of immune cells and their interactions with cutaneous parenchymal cells can markedly advance our comprehension of the mechanisms underlying the onset and recurrence of psoriasis. In this comprehensive review, we present an overview of recent applications of single-cell technologies in psoriasis, aiming to improve our understanding of the underlying mechanisms of this disorder.
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Affiliation(s)
- Niannian Cui
- First School of Clinical Medicine, Anhui Medical University, Hefei 230032, China
| | - Xiaoqing Xu
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230031, China; Institute of Dermatology, Anhui Medical University, Hefei, Anhui 230022, China; The Key Laboratory of Dermatology, Ministry of Education, Anhui Medical University, Hefei, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230022, China
| | - Fusheng Zhou
- Department of Dermatology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230031, China; Institute of Dermatology, Anhui Medical University, Hefei, Anhui 230022, China; The Key Laboratory of Dermatology, Ministry of Education, Anhui Medical University, Hefei, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230022, China.
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3
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Sun X, Yu Y, Qian K, Wang J, Huang L. Recent Progress in Mass Spectrometry-Based Single-Cell Metabolic Analysis. SMALL METHODS 2024; 8:e2301317. [PMID: 38032130 DOI: 10.1002/smtd.202301317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/10/2023] [Indexed: 12/01/2023]
Abstract
Single-cell analysis enables the measurement of biomolecules at the level of individual cells, facilitating in-depth investigations into cellular heterogeneity and precise interpretation of the related biological mechanisms. Among these biomolecules, cellular metabolites exhibit remarkable sensitivity to environmental and biochemical changes, unveiling a hidden world underlying cellular heterogeneity and allowing for the determination of cell physiological states. However, the metabolic analysis of single cells is challenging due to the extremely low concentrations, substantial content variations, and rapid turnover rates of cellular metabolites. Mass spectrometry (MS), characterized by its high sensitivity, wide dynamic range, and excellent selectivity, is employed in single-cell metabolic analysis. This review focuses on recent advances and applications of MS-based single-cell metabolic analysis, encompassing three key steps of single-cell isolation, detection, and application. It is anticipated that MS will bring profound implications in biomedical practices, serving as advanced tools to depict the single-cell metabolic landscape.
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Affiliation(s)
- Xuming Sun
- Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
- Shanghai Institute of Thoracic Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, 453003, P. R. China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang Medical University, Xinxiang, 453003, P. R. China
- Xinxiang Key Laboratory of Neurobiosensor, Xinxiang Medical University, Xinxiang, 453003, P. R. China
| | - Yi Yu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, 453003, P. R. China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang Medical University, Xinxiang, 453003, P. R. China
- Xinxiang Key Laboratory of Neurobiosensor, Xinxiang Medical University, Xinxiang, 453003, P. R. China
| | - Kun Qian
- School of Biomedical Engineering, Institute of Medical Robotics and Med X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Jiayi Wang
- Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
- Shanghai Institute of Thoracic Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
| | - Lin Huang
- Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
- Shanghai Institute of Thoracic Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, P. R. China
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4
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Pattaroni C, Begka C, Cardwell B, Jaffar J, Macowan M, Harris NL, Westall GP, Marsland BJ. Multi-omics integration reveals a nonlinear signature that precedes progression of lung fibrosis. Clin Transl Immunology 2024; 13:e1485. [PMID: 38269243 PMCID: PMC10807351 DOI: 10.1002/cti2.1485] [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: 08/28/2023] [Revised: 12/11/2023] [Accepted: 01/09/2024] [Indexed: 01/26/2024] Open
Abstract
Objectives Idiopathic pulmonary fibrosis (IPF) is a devastating progressive interstitial lung disease with poor outcomes. While decades of research have shed light on pathophysiological mechanisms associated with the disease, our understanding of the early molecular events driving IPF and its progression is limited. With this study, we aimed to model the leading edge of fibrosis using a data-driven approach. Methods Multiple omics modalities (transcriptomics, metabolomics and lipidomics) of healthy and IPF lung explants representing different stages of fibrosis were combined using an unbiased approach. Multi-Omics Factor Analysis of datasets revealed latent factors specifically linked with established fibrotic disease (Factor1) and disease progression (Factor2). Results Features characterising Factor1 comprised well-established hallmarks of fibrotic disease such as defects in surfactant, epithelial-mesenchymal transition, extracellular matrix deposition, mitochondrial dysfunction and purine metabolism. Comparatively, Factor2 identified a signature revealing a nonlinear trajectory towards disease progression. Molecular features characterising Factor2 included genes related to transcriptional regulation of cell differentiation, ciliogenesis and a subset of lipids from the endocannabinoid class. Machine learning models, trained upon the top transcriptomics features of each factor, accurately predicted disease status and progression when tested on two independent datasets. Conclusion This multi-omics integrative approach has revealed a unique signature which may represent the inflection point in disease progression, representing a promising avenue for the identification of therapeutic targets aimed at addressing the progressive nature of the disease.
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Affiliation(s)
- Céline Pattaroni
- Department of Immunology, School of Translational MedicineMonash UniversityMelbourneVICAustralia
| | - Christina Begka
- Department of Immunology, School of Translational MedicineMonash UniversityMelbourneVICAustralia
| | - Bailey Cardwell
- Department of Immunology, School of Translational MedicineMonash UniversityMelbourneVICAustralia
| | - Jade Jaffar
- Department of Immunology, School of Translational MedicineMonash UniversityMelbourneVICAustralia
| | - Matthew Macowan
- Department of Immunology, School of Translational MedicineMonash UniversityMelbourneVICAustralia
| | - Nicola L Harris
- Department of Immunology, School of Translational MedicineMonash UniversityMelbourneVICAustralia
| | - Glen P Westall
- Department of Immunology, School of Translational MedicineMonash UniversityMelbourneVICAustralia
- Department of Respiratory MedicineAlfred HospitalMelbourneVICAustralia
| | - Benjamin J Marsland
- Department of Immunology, School of Translational MedicineMonash UniversityMelbourneVICAustralia
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5
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Jiang Z, He J, Zhang B, Wang L, Long C, Zhao B, Yang Y, Du L, Luo W, Hu J, Hong X. A Potential "Anti-Warburg Effect" in Circulating Tumor Cell-mediated Metastatic Progression? Aging Dis 2024:AD.2023.1227. [PMID: 38300633 DOI: 10.14336/ad.2023.1227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 12/27/2023] [Indexed: 02/02/2024] Open
Abstract
Metabolic reprogramming is a defining hallmark of cancer metastasis, warranting thorough exploration. The tumor-promoting function of the "Warburg Effect", marked by escalated glycolysis and restrained mitochondrial activity, is widely acknowledged. Yet, the functional significance of mitochondria-mediated oxidative phosphorylation (OXPHOS) during metastasis remains controversial. Circulating tumor cells (CTCs) are considered metastatic precursors that detach from primary or secondary sites and harbor the potential to seed distant metastases through hematogenous dissemination. A comprehensive metabolic characterization of CTCs faces formidable obstacles, including the isolation of these rare cells from billions of blood cells, coupled with the complexities of ex vivo-culturing of CTC lines or the establishment of CTC-derived xenograft models (CDX). This review summarized the role of the "Warburg Effect" in both tumorigenesis and CTC-mediated metastasis. Intriguingly, bioinformatic analysis of single-CTC transcriptomic studies unveils a potential OXPHOS dominance over Glycolysis signature genes across several important cancer types. From these observations, we postulate a potential "Anti-Warburg Effect" (AWE) in CTCs-a metabolic shift bridging primary tumors and metastases. The observed AWE could be clinically important as they are significantly correlated with therapeutic response in melanoma and prostate patients. Thus, unraveling dynamic metabolic regulations within CTC populations might reveal an additional layer of regulatory complexities of cancer metastasis, providing an avenue for innovative anti-metastasis therapies.
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Affiliation(s)
- Zhuofeng Jiang
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China
- Cancer Research Institute, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen Third People's Hospital, National Clinical Research Center for Infectious Diseases, Shenzhen, China
| | - Jiapeng He
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China
- Cancer Research Institute, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen Third People's Hospital, National Clinical Research Center for Infectious Diseases, Shenzhen, China
| | - Binyu Zhang
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China
- Cancer Research Institute, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen Third People's Hospital, National Clinical Research Center for Infectious Diseases, Shenzhen, China
| | - Liping Wang
- Department of Oncology, Southern University of Science and Technology Hospital, Shenzhen, Guangdong, China
| | - Chunhao Long
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Boxi Zhao
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Yufan Yang
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Longxiang Du
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Weiren Luo
- Cancer Research Institute, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen Third People's Hospital, National Clinical Research Center for Infectious Diseases, Shenzhen, China
| | - Jianyang Hu
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Xin Hong
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China
- Key University Laboratory of Metabolism and Health of Guangdong, Southern University of Science and Technology, Shenzhen, Guangdong, China
- Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, Guangdong, China
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6
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Cooke JP, Lai L. Transflammation in tissue regeneration and response to injury: How cell-autonomous inflammatory signaling mediates cell plasticity. Adv Drug Deliv Rev 2023; 203:115118. [PMID: 37884127 PMCID: PMC10842620 DOI: 10.1016/j.addr.2023.115118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 08/01/2023] [Accepted: 10/23/2023] [Indexed: 10/28/2023]
Abstract
Inflammation is a first responder against injury and infection and is also critical for the regeneration and repair of tissue after injury. The role of professional immune cells in tissue healing is well characterized. Professional immune cells respond to pathogens with humoral and cytotoxic responses; remove cellular debris through efferocytosis; secrete angiogenic cytokines and growth factors to repair the microvasculature and parenchyma. However, non-immune cells are also capable of responding to damage or pathogens. Non-immune somatic cells express pattern recognition receptors (PRRs) to detect pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs). The PRRs activation leads to the release of inflammatory cytokines required for tissue defense and repair. Notably, the activation of PRRs also triggers epigenetic changes that promote DNA accessibility and cellular plasticity. Thus, non-immune cells directly respond to the local inflammatory cues and can undergo phenotypic modifications or even cell lineage transitions to facilitate tissue regeneration. This review will focus on the novel role of cell-autonomous inflammatory signaling in mediating cell plasticity, a process which is termed transflammation. We will discuss the regulation of this process by changes in the functions and expression levels of epigenetic modifiers, as well as metabolic and ROS/RNS-mediated epigenetic modulation of DNA accessibility during cell fate transition. We will highlight the recent technological developments in detecting cell plasticity and potential therapeutic applications of transflammation in tissue regeneration.
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Affiliation(s)
- John P Cooke
- Department of Cardiovascular Sciences, Houston Methodist Research Institute, Houston, TX, United States
| | - Li Lai
- Department of Cardiovascular Sciences, Houston Methodist Research Institute, Houston, TX, United States.
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7
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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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8
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Schirmer M, Dusny C. Microbial single-cell mass spectrometry: status, challenges, and prospects. Curr Opin Biotechnol 2023; 83:102977. [PMID: 37515936 DOI: 10.1016/j.copbio.2023.102977] [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: 03/16/2023] [Revised: 07/04/2023] [Accepted: 07/05/2023] [Indexed: 07/31/2023]
Abstract
Single-cell analysis uncovers phenotypic differences between cells in a population and dissects their individual physiological states and differences on all omics levels from genome to phenome. Spectrometric observation allows label-free analysis of the metabolome and proteome of individual cells, but is still mainly limited to the analysis of mammalian single cells. Recent progress in mass spectrometry approaches now enables the analysis of microbial single cells - mainly by miniaturizing cell handling, incubation, and improving chip-coupling concepts for analyte ionization by interfacing microfluidic chips and mass spectrometers. This review aims at distilling the enabling principles behind microbial single-cell mass spectrometry and puts them into perspective for the future of the field.
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Affiliation(s)
- Martin Schirmer
- Department of Solar Materials - Microscale Analysis and Engineering, Helmholtz-Centre for Environmental Research - UFZ Leipzig, Leizpig, Germany
| | - Christian Dusny
- Department of Solar Materials - Microscale Analysis and Engineering, Helmholtz-Centre for Environmental Research - UFZ Leipzig, Leizpig, Germany.
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9
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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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10
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Aitmanaitė L, Širmonaitis K, Russo G. Microbiomes, Their Function, and Cancer: How Metatranscriptomics Can Close the Knowledge Gap. Int J Mol Sci 2023; 24:13786. [PMID: 37762088 PMCID: PMC10531294 DOI: 10.3390/ijms241813786] [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: 08/07/2023] [Revised: 08/28/2023] [Accepted: 08/30/2023] [Indexed: 09/29/2023] Open
Abstract
The interaction between the microbial communities in the human body and the onset and progression of cancer has not been investigated until recently. The vast majority of the metagenomics research in this area has concentrated on the composition of microbiomes, attempting to link the overabundance or depletion of certain microorganisms to cancer proliferation, metastatic behaviour, and its resistance to therapies. However, studies elucidating the functional implications of the microbiome activity in cancer patients are still scarce; in particular, there is an overwhelming lack of studies assessing such implications directly, through analysis of the transcriptome of the bacterial community. This review summarises the contributions of metagenomics and metatranscriptomics to the knowledge of the microbial environment associated with several cancers; most importantly, it highlights all the advantages that metatranscriptomics has over metagenomics and suggests how such an approach can be leveraged to advance the knowledge of the cancer bacterial environment.
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Affiliation(s)
| | | | - Giancarlo Russo
- EMBL Partnership Institute for Gene Editing, Life Sciences Center, Vilnius University, LT-10257 Vilnius, Lithuania; (L.A.); (K.Š.)
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11
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Jin Y, Chi J, LoMonaco K, Boon A, Gu H. Recent Review on Selected Xenobiotics and Their Impacts on Gut Microbiome and Metabolome. Trends Analyt Chem 2023; 166:117155. [PMID: 37484879 PMCID: PMC10361410 DOI: 10.1016/j.trac.2023.117155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
As it is well known, the gut is one of the primary sites in any host for xenobiotics, and the many microbial metabolites responsible for the interactions between the gut microbiome and the host. However, there is a growing concern about the negative impacts on human health induced by toxic xenobiotics. Metabolomics, broadly including lipidomics, is an emerging approach to studying thousands of metabolites in parallel. In this review, we summarized recent advancements in mass spectrometry (MS) technologies in metabolomics. In addition, we reviewed recent applications of MS-based metabolomics for the investigation of toxic effects of xenobiotics on microbial and host metabolism. It was demonstrated that metabolomics, gut microbiome profiling, and their combination have a high potential to identify metabolic and microbial markers of xenobiotic exposure and determine its mechanism. Further, there is increasing evidence supporting that reprogramming the gut microbiome could be a promising approach to the intervention of xenobiotic toxicity.
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Affiliation(s)
- Yan Jin
- Center for Translational Science, Florida International University, Port St. Lucie, FL 34987, USA
| | - Jinhua Chi
- Center for Translational Science, Florida International University, Port St. Lucie, FL 34987, USA
| | - Kaelene LoMonaco
- Center for Translational Science, Florida International University, Port St. Lucie, FL 34987, USA
| | - Alexandria Boon
- Center for Translational Science, Florida International University, Port St. Lucie, FL 34987, USA
| | - Haiwei Gu
- Center for Translational Science, Florida International University, Port St. Lucie, FL 34987, USA
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12
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Kelliher JM, Robinson AJ, Longley R, Johnson LYD, Hanson BT, Morales DP, Cailleau G, Junier P, Bonito G, Chain PSG. The endohyphal microbiome: current progress and challenges for scaling down integrative multi-omic microbiome research. MICROBIOME 2023; 11:192. [PMID: 37626434 PMCID: PMC10463477 DOI: 10.1186/s40168-023-01634-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 07/29/2023] [Indexed: 08/27/2023]
Abstract
As microbiome research has progressed, it has become clear that most, if not all, eukaryotic organisms are hosts to microbiomes composed of prokaryotes, other eukaryotes, and viruses. Fungi have only recently been considered holobionts with their own microbiomes, as filamentous fungi have been found to harbor bacteria (including cyanobacteria), mycoviruses, other fungi, and whole algal cells within their hyphae. Constituents of this complex endohyphal microbiome have been interrogated using multi-omic approaches. However, a lack of tools, techniques, and standardization for integrative multi-omics for small-scale microbiomes (e.g., intracellular microbiomes) has limited progress towards investigating and understanding the total diversity of the endohyphal microbiome and its functional impacts on fungal hosts. Understanding microbiome impacts on fungal hosts will advance explorations of how "microbiomes within microbiomes" affect broader microbial community dynamics and ecological functions. Progress to date as well as ongoing challenges of performing integrative multi-omics on the endohyphal microbiome is discussed herein. Addressing the challenges associated with the sample extraction, sample preparation, multi-omic data generation, and multi-omic data analysis and integration will help advance current knowledge of the endohyphal microbiome and provide a road map for shrinking microbiome investigations to smaller scales. Video Abstract.
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Affiliation(s)
| | | | - Reid Longley
- Los Alamos National Laboratory, Los Alamos, NM, USA
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13
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Gao P. Exploring Single-Cell Exposomics by Mass Spectrometry. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:12201-12209. [PMID: 37561608 PMCID: PMC10448745 DOI: 10.1021/acs.est.3c04524] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Indexed: 08/12/2023]
Abstract
Single-cell exposomics, a revolutionary approach that investigates cell-environment interactions at cellular and subcellular levels, stands distinct from conventional bulk exposomics. Leveraging advancements in mass spectrometry, it provides a detailed perspective on cellular dynamics, interactions, and responses to environmental stimuli and their impacts on human health. This work delves into this innovative realm, highlighting the nuanced interplay between environmental stressors and biological responses at cellular and subcellular levels. The application of spatial mass spectrometry in single-cell exposomics is discussed, revealing the intricate spatial organization and molecular composition within individual cells. Cell-type-specific exposomics, shedding light on distinct susceptibilities and adaptive strategies of various cell types to environmental exposures, is also examined. The Perspective further emphasizes the integration with molecular and cellular biology approaches to validate hypotheses derived from single-cell exposomics in a comprehensive biological context. Looking toward the future, we anticipate continued technological advancements and convergence with other -omics approaches and discuss implications for environmental health research, disease progression studies, and precision medicine. The final emphasis is on the need for robust computational tools and interdisciplinary collaboration to fully leverage the potential of single-cell exposomics, acknowledging the complexities inherent to this paradigm.
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Affiliation(s)
- Peng Gao
- Department
of Environmental and Occupational Health and Department of Civil and
Environmental Engineering, University of
Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
- UPMC
Hillman Cancer Center, Pittsburgh, Pennsylvania 15232, United States
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14
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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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15
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Rathore D, Marino MJ, Nita-Lazar A. Omics and systems view of innate immune pathways. Proteomics 2023; 23:e2200407. [PMID: 37269203 DOI: 10.1002/pmic.202200407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/16/2023] [Accepted: 05/23/2023] [Indexed: 06/04/2023]
Abstract
Multiomics approaches to studying systems biology are very powerful techniques that can elucidate changes in the genomic, transcriptomic, proteomic, and metabolomic levels within a cell type in response to an infection. These approaches are valuable for understanding the mechanisms behind disease pathogenesis and how the immune system responds to being challenged. With the emergence of the COVID-19 pandemic, the importance and utility of these tools have become evident in garnering a better understanding of the systems biology within the innate and adaptive immune response and for developing treatments and preventative measures for new and emerging pathogens that pose a threat to human health. In this review, we focus on state-of-the-art omics technologies within the scope of innate immunity.
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Affiliation(s)
- Deepali Rathore
- Functional Cellular Networks Section, Laboratory of Immune Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Matthew J Marino
- Functional Cellular Networks Section, Laboratory of Immune Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Aleksandra Nita-Lazar
- Functional Cellular Networks Section, Laboratory of Immune Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
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16
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Zhou N, Wang Y, Zhang Z, Feng W, Liu T, Cao Y, Zhang J, Zhang B, Zheng X, Li K. Characterizing the specific mechanism of series processed Coptidis Rhizoma by multi-organ metabolomics combined with network pharmacology and molecular docking. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2023; 114:154804. [PMID: 37031638 DOI: 10.1016/j.phymed.2023.154804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 03/20/2023] [Accepted: 04/02/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND After being processed with different excipients, the clinical application of Coptidis Rhizoma (CR) is differentially investigated. However, the underlying mechanism and material basis are not clear, and there is a lack of attention to the collaborative working mode of herbal medicine during exploration. PURPOSE To characterize the specific mechanism of wine/zingiberis rhizoma recens/euodiae fructus processed CR (wCR/zCR/eCR) and to investigate the role of excipients during processing. METHODS The multi-organ metabolomics approach was employed to explore the target organs of wCR/zCR/eCR and multiple pathways being triggered in each organ. The tissue distribution of CR and wCR/zCR/eCR components was compared to indicate the material basis of efficacy change after processing. Further, the network pharmacology study coupled with experimental validation was conducted to support metabolomic research and predicted active ingredients and core targets, and the molecular docking coupled with binding test was performed to identify the binding between active ingredient and core target. RESULTS The multi-organ metabolomics and network pharmacology study elucidated the intervening effect of wCR on heart/lung, zCR on stomach/colon, and eCR on liver/colon/stomach. Combined with molecular docking, binding test and tissue distribution studies, the specific mechanism was as follows: the wine made iso-quinoline alkaloids in CR more likely to accumulate in heart/lung, thus triggering the core targets of PTGS2, NOS2, ESR1 and SLC6A4 in heart/lung, and thereby highlighting the detoxifying and cardiopulmonary protective effect of wCR. The zingiberis rhizoma recens and euodiae fructus made organic acids in CR more likely to accumulate in stomach/colon and liver/colon/stomach respectively, thus triggering the core targets of ACTB, TNF and PRKCA in stomach/colon, the core targets of ACTB, TNF, PRKCA and GPT in stomach/colon/liver, and thereby highlighting the improving effect of zCR/eCR on digestive function. CONCLUSION Iso-quinoline alkaloids were the material basis of CR for anti-inflammation, and organic acids were mainly responsible for regulating gastrointestinal function. Due to the influence of excipients on the accumulation tendency of CR components, the differentially highlighted application of wCR/zCR/eCR was achieved. These findings propose a novel strategy for processing mechanism research.
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Affiliation(s)
- Ning Zhou
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, People's Republic of China; Co-construction Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases by Henan & Education Ministry of P.R. China, Zhengzhou 450046, People's Republic of China
| | - Yongxiang Wang
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, People's Republic of China; The Engineering and Technology Center for Chinese Medicine Development of Henan Province, Zhengzhou 450046, People's Republic of China
| | - Zhenkai Zhang
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, People's Republic of China; The Engineering and Technology Center for Chinese Medicine Development of Henan Province, Zhengzhou 450046, People's Republic of China
| | - Weisheng Feng
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, People's Republic of China; Co-construction Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases by Henan & Education Ministry of P.R. China, Zhengzhou 450046, People's Republic of China
| | - Tong Liu
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, People's Republic of China
| | - Yumin Cao
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, People's Republic of China
| | - Jinying Zhang
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, People's Republic of China
| | - Bingxian Zhang
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, People's Republic of China
| | - Xiaoke Zheng
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, People's Republic of China; Co-construction Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases by Henan & Education Ministry of P.R. China, Zhengzhou 450046, People's Republic of China
| | - Kai Li
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, People's Republic of China; Henan Research Center for Special Processing Technology of Chinese Medicine, Zhengzhou 450046, People's Republic of China
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17
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Daloso DDM, Morais EG, Oliveira E Silva KF, Williams TCR. Cell-type-specific metabolism in plants. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 114:1093-1114. [PMID: 36987968 DOI: 10.1111/tpj.16214] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 03/20/2023] [Accepted: 03/25/2023] [Indexed: 05/31/2023]
Abstract
Every plant organ contains tens of different cell types, each with a specialized function. These functions are intrinsically associated with specific metabolic flux distributions that permit the synthesis of the ATP, reducing equivalents and biosynthetic precursors demanded by the cell. Investigating such cell-type-specific metabolism is complicated by the mosaic of different cells within each tissue combined with the relative scarcity of certain types. However, techniques for the isolation of specific cells, their analysis in situ by microscopy, or modeling of their function in silico have permitted insight into cell-type-specific metabolism. In this review we present some of the methods used in the analysis of cell-type-specific metabolism before describing what we know about metabolism in several cell types that have been studied in depth; (i) leaf source and sink cells; (ii) glandular trichomes that are capable of rapid synthesis of specialized metabolites; (iii) guard cells that must accumulate large quantities of the osmolytes needed for stomatal opening; (iv) cells of seeds involved in storage of reserves; and (v) the mesophyll and bundle sheath cells of C4 plants that participate in a CO2 concentrating cycle. Metabolism is discussed in terms of its principal features, connection to cell function and what factors affect the flux distribution. Demand for precursors and energy, availability of substrates and suppression of deleterious processes are identified as key factors in shaping cell-type-specific metabolism.
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Affiliation(s)
- Danilo de Menezes Daloso
- Lab Plant, Departamento de Bioquímica e Biologia Molecular, Universidade Federal do Ceará, Fortaleza-CA, 60451-970, Brazil
| | - Eva Gomes Morais
- Lab Plant, Departamento de Bioquímica e Biologia Molecular, Universidade Federal do Ceará, Fortaleza-CA, 60451-970, Brazil
| | - Karen Fernanda Oliveira E Silva
- Departamento de Botânica, Instituto de Ciências Biológicas, Universidade de Brasília, Asa Norte, Brasília-DF, 70910-900, Brazil
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18
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Saunders KDG, Lewis HM, Beste DJ, Cexus O, Bailey MJ. Spatial single cell metabolomics: Current challenges and future developments. Curr Opin Chem Biol 2023; 75:102327. [PMID: 37224735 DOI: 10.1016/j.cbpa.2023.102327] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 04/03/2023] [Accepted: 04/24/2023] [Indexed: 05/26/2023]
Abstract
Single cell metabolomics is a rapidly advancing field of bio-analytical chemistry which aims to observe cellular biology with the greatest detail possible. Mass spectrometry imaging and selective cell sampling (e.g. using nanocapillaries) are two common approaches within the field. Recent achievements such as observation of cell-cell interactions, lipids determining cell states and rapid phenotypic identification demonstrate the efficacy of these approaches and the momentum of the field. However, single cell metabolomics can only continue with the same impetus if the universal challenges to the field are met, such as the lack of strategies for standardisation and quantification, and lack of specificity/sensitivity. Mass spectrometry imaging and selective cell sampling come with unique advantages and challenges which, in many cases are complementary to each other. We propose here that the challenges specific to each approach could be ameliorated with collaboration between the two communities driving these approaches.
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Affiliation(s)
| | - Holly-May Lewis
- Department of Chemistry, University of Surrey, Guildford, UK
| | - Dany Jv Beste
- Department of Microbial Sciences, University of Surrey, Guildford, UK
| | - Olivier Cexus
- Faculty of Health & Medical Sciences, University of Surrey, Guildford, UK
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19
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Li C, Wood JC, Vu AH, Hamilton JP, Rodriguez Lopez CE, Payne RME, Serna Guerrero DA, Gase K, Yamamoto K, Vaillancourt B, Caputi L, O'Connor SE, Robin Buell C. Single-cell multi-omics in the medicinal plant Catharanthus roseus. Nat Chem Biol 2023:10.1038/s41589-023-01327-0. [PMID: 37188960 PMCID: PMC10374443 DOI: 10.1038/s41589-023-01327-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 04/04/2023] [Indexed: 05/17/2023]
Abstract
Advances in omics technologies now permit the generation of highly contiguous genome assemblies, detection of transcripts and metabolites at the level of single cells and high-resolution determination of gene regulatory features. Here, using a complementary, multi-omics approach, we interrogated the monoterpene indole alkaloid (MIA) biosynthetic pathway in Catharanthus roseus, a source of leading anticancer drugs. We identified clusters of genes involved in MIA biosynthesis on the eight C. roseus chromosomes and extensive gene duplication of MIA pathway genes. Clustering was not limited to the linear genome, and through chromatin interaction data, MIA pathway genes were present within the same topologically associated domain, permitting the identification of a secologanin transporter. Single-cell RNA-sequencing revealed sequential cell-type-specific partitioning of the leaf MIA biosynthetic pathway that, when coupled with a single-cell metabolomics approach, permitted the identification of a reductase that yields the bis-indole alkaloid anhydrovinblastine. We also revealed cell-type-specific expression in the root MIA pathway.
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Affiliation(s)
- Chenxin Li
- Center for Applied Genetic Technologies, University of Georgia, Athens, GA, USA
| | - Joshua C Wood
- Center for Applied Genetic Technologies, University of Georgia, Athens, GA, USA
| | - Anh Hai Vu
- Department of Natural Product Biosynthesis, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - John P Hamilton
- Center for Applied Genetic Technologies, University of Georgia, Athens, GA, USA
| | | | - Richard M E Payne
- The John Innes Centre, Department of Biological Chemistry, Norwich Research Park, Norwich, UK
| | | | - Klaus Gase
- Department of Natural Product Biosynthesis, Max Planck Institute for Chemical Ecology, Jena, Germany
| | - Kotaro Yamamoto
- School of Science, Association of International Arts and Science, Yokohama City University, Yokohama, Japan
| | | | - Lorenzo Caputi
- Department of Natural Product Biosynthesis, Max Planck Institute for Chemical Ecology, Jena, Germany.
| | - Sarah E O'Connor
- Department of Natural Product Biosynthesis, Max Planck Institute for Chemical Ecology, Jena, Germany.
| | - C Robin Buell
- Center for Applied Genetic Technologies, University of Georgia, Athens, GA, USA.
- Department of Crop and Soil Sciences, University of Georgia, Athens, GA, USA.
- Institute of Plant Breeding, Genetics and Genomics, University of Georgia, Athens, GA, USA.
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20
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Flores-Tornero M, Becker JD. 50 years of sperm cell isolations: from structural to omic studies. JOURNAL OF EXPERIMENTAL BOTANY 2023:erad117. [PMID: 37025026 DOI: 10.1093/jxb/erad117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Indexed: 06/19/2023]
Abstract
The fusion of male and female gametes is a fundamental process in the perpetuation and diversification of species. During the last 50 years, significant efforts have been made to isolate and characterize sperm cells from flowering plants, and to identify how these cells interact with female gametes to achieve double fertilization. The first techniques and analytical approaches not only provided structural and biochemical characterizations of plant sperm cells but also paved the way for in vitro fertilization studies. Further technological advances then led to unique insights into sperm biology at transcriptomic, proteomic and epigenetic level. Starting with a historical overview of sperm cell isolation techniques, we provide examples of how these contributed to create our current knowledge of sperm cell biology, and point out remaining challenges.
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Affiliation(s)
- María Flores-Tornero
- Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Av. da República, Oeiras, 2780-157 Portugal
| | - Jörg D Becker
- Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Av. da República, Oeiras, 2780-157 Portugal
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21
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Yang J, Chen Y, Jing Y, Green MR, Han L. Advancing CAR T cell therapy through the use of multidimensional omics data. Nat Rev Clin Oncol 2023; 20:211-228. [PMID: 36721024 DOI: 10.1038/s41571-023-00729-2] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/09/2023] [Indexed: 02/01/2023]
Abstract
Despite the notable success of chimeric antigen receptor (CAR) T cell therapies in the treatment of certain haematological malignancies, challenges remain in optimizing CAR designs and cell products, improving response rates, extending the durability of remissions, reducing toxicity and broadening the utility of this therapeutic modality to other cancer types. Data from multidimensional omics analyses, including genomics, epigenomics, transcriptomics, T cell receptor-repertoire profiling, proteomics, metabolomics and/or microbiomics, provide unique opportunities to dissect the complex and dynamic multifactorial phenotypes, processes and responses of CAR T cells as well as to discover novel tumour targets and pathways of resistance. In this Review, we summarize the multidimensional cellular and molecular profiling technologies that have been used to advance our mechanistic understanding of CAR T cell therapies. In addition, we discuss current applications and potential strategies leveraging multi-omics data to identify optimal target antigens and other molecular features that could be exploited to enhance the antitumour activity and minimize the toxicity of CAR T cell therapy. Indeed, fully utilizing multi-omics data will provide new insights into the biology of CAR T cell therapy, further accelerate the development of products with improved efficacy and safety profiles, and enable clinicians to better predict and monitor patient responses.
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Affiliation(s)
- Jingwen Yang
- Center for Epigenetics and Disease Prevention, Institute of Biosciences and Technology, Texas A&M University, Houston, TX, USA
| | - Yamei Chen
- Center for Epigenetics and Disease Prevention, Institute of Biosciences and Technology, Texas A&M University, Houston, TX, USA
| | - Ying Jing
- Department of Biochemistry and Molecular Biology, The University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX, USA
| | - Michael R Green
- Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Leng Han
- Center for Epigenetics and Disease Prevention, Institute of Biosciences and Technology, Texas A&M University, Houston, TX, USA.
- Department of Translational Medical Sciences, College of Medicine, Texas A&M University, Houston, TX, USA.
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22
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Wang RS, Maron BA, Loscalzo J. Multiomics Network Medicine Approaches to Precision Medicine and Therapeutics in Cardiovascular Diseases. Arterioscler Thromb Vasc Biol 2023; 43:493-503. [PMID: 36794589 PMCID: PMC10038904 DOI: 10.1161/atvbaha.122.318731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/30/2023] [Indexed: 02/17/2023]
Abstract
Cardiovascular diseases (CVD) are the leading cause of death worldwide and display complex phenotypic heterogeneity caused by many convergent processes, including interactions between genetic variation and environmental factors. Despite the identification of a large number of associated genes and genetic loci, the precise mechanisms by which these genes systematically influence the phenotypic heterogeneity of CVD are not well understood. In addition to DNA sequence, understanding the molecular mechanisms of CVD requires data from other omics levels, including the epigenome, the transcriptome, the proteome, as well as the metabolome. Recent advances in multiomics technologies have opened new precision medicine opportunities beyond genomics that can guide precise diagnosis and personalized treatment. At the same time, network medicine has emerged as an interdisciplinary field that integrates systems biology and network science to focus on the interactions among biological components in health and disease, providing an unbiased framework through which to integrate systematically these multiomics data. In this review, we briefly present such multiomics technologies, including bulk omics and single-cell omics technologies, and discuss how they can contribute to precision medicine. We then highlight network medicine-based integration of multiomics data for precision medicine and therapeutics in CVD. We also include a discussion of current challenges, potential limitations, and future directions in the study of CVD using multiomics network medicine approaches.
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Affiliation(s)
- Rui-Sheng Wang
- Division of Cardiovascular Medicine
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | | | - Joseph Loscalzo
- Division of Cardiovascular Medicine
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
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23
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Danzi F, Pacchiana R, Mafficini A, Scupoli MT, Scarpa A, Donadelli M, Fiore A. To metabolomics and beyond: a technological portfolio to investigate cancer metabolism. Signal Transduct Target Ther 2023; 8:137. [PMID: 36949046 PMCID: PMC10033890 DOI: 10.1038/s41392-023-01380-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/08/2023] [Accepted: 02/15/2023] [Indexed: 03/24/2023] Open
Abstract
Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.
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Affiliation(s)
- Federica Danzi
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy
| | - Raffaella Pacchiana
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy
| | - Andrea Mafficini
- Department of Diagnostics and Public Health, University of Verona, Verona, Italy
| | - Maria T Scupoli
- Department of Neurosciences, Biomedicine and Movement Sciences, Biology and Genetics Section, University of Verona, Verona, Italy
| | - Aldo Scarpa
- Department of Diagnostics and Public Health, University of Verona, Verona, Italy
- ARC-NET Research Centre, University and Hospital Trust of Verona, Verona, Italy
| | - Massimo Donadelli
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy.
| | - Alessandra Fiore
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy
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24
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Gonzales LISA, Qiao JW, Buffier AW, Rogers LJ, Suchowerska N, McKenzie DR, Kwan AH. An omics approach to delineating the molecular mechanisms that underlie the biological effects of physical plasma. BIOPHYSICS REVIEWS 2023; 4:011312. [PMID: 38510160 PMCID: PMC10903421 DOI: 10.1063/5.0089831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 02/24/2023] [Indexed: 03/22/2024]
Abstract
The use of physical plasma to treat cancer is an emerging field, and interest in its applications in oncology is increasing rapidly. Physical plasma can be used directly by aiming the plasma jet onto cells or tissue, or indirectly, where a plasma-treated solution is applied. A key scientific question is the mechanism by which physical plasma achieves selective killing of cancer over normal cells. Many studies have focused on specific pathways and mechanisms, such as apoptosis and oxidative stress, and the role of redox biology. However, over the past two decades, there has been a rise in omics, the systematic analysis of entire collections of molecules in a biological entity, enabling the discovery of the so-called "unknown unknowns." For example, transcriptomics, epigenomics, proteomics, and metabolomics have helped to uncover molecular mechanisms behind the action of physical plasma, revealing critical pathways beyond those traditionally associated with cancer treatments. This review showcases a selection of omics and then summarizes the insights gained from these studies toward understanding the biological pathways and molecular mechanisms implicated in physical plasma treatment. Omics studies have revealed how reactive species generated by plasma treatment preferentially affect several critical cellular pathways in cancer cells, resulting in epigenetic, transcriptional, and post-translational changes that promote cell death. Finally, this review considers the outlook for omics in uncovering both synergies and antagonisms with other common cancer therapies, as well as in overcoming challenges in the clinical translation of physical plasma.
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Affiliation(s)
- Lou I. S. A. Gonzales
- School of Life and Environmental Sciences, The University of Sydney, NSW 2006, Australia
| | - Jessica W. Qiao
- School of Life and Environmental Sciences, The University of Sydney, NSW 2006, Australia
| | - Aston W. Buffier
- School of Life and Environmental Sciences, The University of Sydney, NSW 2006, Australia
| | | | | | | | - Ann H. Kwan
- Author to whom correspondence should be addressed:
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25
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Arruda MAZ, da Silva ABS, Kato LS. There Is Plenty of Room in Plant Science: Nanobiotechnology as an Emerging Area Applied to Somatic Embryogenesis. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:3651-3657. [PMID: 36786777 DOI: 10.1021/acs.jafc.2c08065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Somatic embryogenesis is an essential technology for high productivity in plant culture, and with the advent of nanotechnology, the synergism between these areas could be the answer to developing concepts involving Agriculture 4.0. This perspective permeates both areas, presenting the opportunities and challenges for the consolidation of ideas involving the application of nanoparticles to micropropagation processes (callus induction, preservation, growing, and modification, among others) and also to the production of byproducts (such as biosynthesis of nanoparticles and production of secondary metabolites). Nanotoxicological aspects are also emphasized as well as up-to-date instrumentation involved in these studies.
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Affiliation(s)
- Marco Aurélio Zezzi Arruda
- Spectrometry, Sample Preparation and Mechanization Group, Institute of Chemistry, University of Campinas (Unicamp), Post Office Box 6154, Campinas, São Paulo 13083-970, Brazil
- National Institute of Science and Technology for Bioanalytics, Institute of Chemistry, University of Campinas (Unicamp), Post Office Box 6154, Campinas, São Paulo 13083-970, Brazil
| | - Ana Beatriz Santos da Silva
- Spectrometry, Sample Preparation and Mechanization Group, Institute of Chemistry, University of Campinas (Unicamp), Post Office Box 6154, Campinas, São Paulo 13083-970, Brazil
- National Institute of Science and Technology for Bioanalytics, Institute of Chemistry, University of Campinas (Unicamp), Post Office Box 6154, Campinas, São Paulo 13083-970, Brazil
| | - Lilian Seiko Kato
- Spectrometry, Sample Preparation and Mechanization Group, Institute of Chemistry, University of Campinas (Unicamp), Post Office Box 6154, Campinas, São Paulo 13083-970, Brazil
- National Institute of Science and Technology for Bioanalytics, Institute of Chemistry, University of Campinas (Unicamp), Post Office Box 6154, Campinas, São Paulo 13083-970, Brazil
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26
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Ma S, Leng Y, Li X, Meng Y, Yin Z, Hang W. High spatial resolution mass spectrometry imaging for spatial metabolomics: Advances, challenges, and future perspectives. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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Ali A, Davidson S, Fraenkel E, Gilmore I, Hankemeier T, Kirwan JA, Lane AN, Lanekoff I, Larion M, McCall LI, Murphy M, Sweedler JV, Zhu C. Single cell metabolism: current and future trends. Metabolomics 2022; 18:77. [PMID: 36181583 PMCID: PMC10063251 DOI: 10.1007/s11306-022-01934-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 09/05/2022] [Indexed: 11/29/2022]
Abstract
Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.
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Affiliation(s)
- Ahmed Ali
- Leiden Academic Centre for Drug Research, University of Leiden, Gorlaeus Building Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Shawn Davidson
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Ernest Fraenkel
- Department of Biological Engineering and the Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ian Gilmore
- National Physical Laboratory, Teddington, TW11 0LW, Middlesex, UK
| | - Thomas Hankemeier
- Leiden Academic Centre for Drug Research, University of Leiden, Room number GW4.07, Gorlaeus Building, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Jennifer A Kirwan
- Berlin Institute of Health, Metabolomics Platform, Translational Research Unit of the Charite-Universitätsmedizin Berlin, Anna-Louisa-Karsch-Str 2, 10178, Berlin, Germany
| | - Andrew N Lane
- Department of Toxicology and Cancer Biology, and Center for Environmental and Systems Biochemistry, University of Kentucky, 789 S. Limestone St, Lexington, KY, 40536, USA.
| | - Ingela Lanekoff
- Department of Chemistry-BMC, Uppsala University, Husargatan 3 (576), 751 23, Uppsala, Sweden
| | - Mioara Larion
- Center for Cancer Research, National Cancer Institute, Building 37, Room 1136A, Bethesda, MD, 20892, USA
| | - Laura-Isobel McCall
- Department of Chemistry & Biochemistry, Department of Microbiology and Plant Biology, Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, 101 Stephenson Parkway, room 3750, Norman, OK, 73019-5251, USA
| | - Michael Murphy
- Departments of Biological Engineering, Department of Electrical Engineering, and Computer Science and the Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, USA
| | - Jonathan V Sweedler
- Department of Chemistry, and the Beckman Institute, University of Illinois Urbana-Champaign, 505 South Mathews Avenue, Urbana, IL, 61801, USA
| | - Caigang Zhu
- Department of Biomedical Engineering, University of Kentucky, Lexington, KY, 40536, USA
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Yu RJ, Hu YX, Chen KL, Gu Z, Ying YL, Long YT. Confined Nanopipet as a Versatile Tool for Precise Single Cell Manipulation. Anal Chem 2022; 94:12948-12953. [DOI: 10.1021/acs.analchem.2c02415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Ru-Jia Yu
- State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, People’s Republic of China
- Chemistry and Biomedicine Innovation Center, Nanjing University, Nanjing 210023, People’s Republic of China
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, People’s Republic of China
| | - Yong-Xu Hu
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, People’s Republic of China
| | - Ke-Le Chen
- State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, People’s Republic of China
| | - Zhen Gu
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, People’s Republic of China
| | - Yi-Lun Ying
- State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, People’s Republic of China
- Chemistry and Biomedicine Innovation Center, Nanjing University, Nanjing 210023, People’s Republic of China
| | - Yi-Tao Long
- State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, People’s Republic of China
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Qi F, Cao Y, Zhang S, Zhang Z. Single-cell analysis of the adaptive immune response to SARS-CoV-2 infection and vaccination. Front Immunol 2022; 13:964976. [PMID: 36119105 PMCID: PMC9478577 DOI: 10.3389/fimmu.2022.964976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/10/2022] [Indexed: 12/04/2022] Open
Abstract
Amid the ongoing Coronavirus Disease 2019 (COVID-19) pandemic, vaccination and early therapeutic interventions are the most effective means to combat and control the severity of the disease. Host immune responses to SARS-CoV-2 and its variants, particularly adaptive immune responses, should be fully understood to develop improved strategies to implement these measures. Single-cell multi-omic technologies, including flow cytometry, single-cell transcriptomics, and single-cell T-cell receptor (TCR) and B-cell receptor (BCR) profiling, offer a better solution to examine the protective or pathological immune responses and molecular mechanisms associated with SARS-CoV-2 infection, thus providing crucial support for the development of vaccines and therapeutics for COVID-19. Recent reviews have revealed the overall immune landscape of natural SARS-CoV-2 infection, and this review will focus on adaptive immune responses (including T cells and B cells) to SARS-CoV-2 revealed by single-cell multi-omics technologies. In addition, we explore how the single-cell analyses disclose the critical components of immune protection and pathogenesis during SARS-CoV-2 infection through the comparison between the adaptive immune responses induced by natural infection and by vaccination.
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Affiliation(s)
- Furong Qi
- Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People’s Hospital, The Second Affiliated Hospital, School of Medicine, Southern University of Science and Technology, Shenzhen, China
- Shenzhen Key Laboratory of Single-Cell Omics Reasearch and Application, Shenzhen, China
| | - Yingyin Cao
- Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People’s Hospital, The Second Affiliated Hospital, School of Medicine, Southern University of Science and Technology, Shenzhen, China
| | - Shuye Zhang
- Clinical Center for BioTherapy and Institutes of Biomedical Sciences, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zheng Zhang
- Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People’s Hospital, The Second Affiliated Hospital, School of Medicine, Southern University of Science and Technology, Shenzhen, China
- Shenzhen Key Laboratory of Single-Cell Omics Reasearch and Application, Shenzhen, China
- Shenzhen Research Center for Communicable Disease Diagnosis and Treatment of Chinese Academy of Medical Science, Shenzhen, China
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30
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Bourceau P, Michellod D, Geier B, Liebeke M. Spatial metabolomics shows contrasting phosphonolipid distributions in tissues of marine bivalves. PEERJ ANALYTICAL CHEMISTRY 2022. [DOI: 10.7717/peerj-achem.21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Lipids are an integral part of cellular membranes that allow cells to alter stiffness, permeability, and curvature. Among the diversity of lipids, phosphonolipids uniquely contain a phosphonate bond between carbon and phosphorous. Despite this distinctive biochemical characteristic, few studies have explored the biological role of phosphonolipids, although a protective function has been inferred based on chemical and biological stability. We analyzed two species of marine mollusks, the blue mussel Mytilus edulis and pacific oyster Crassostrea gigas, and determined the diversity of phosphonolipids and their distribution in different organs. High-resolution spatial metabolomics revealed that the lipidome varies significantly between tissues within one organ. Despite their chemical similarity, we observed a high heterogeneity of phosphonolipid distributions that originated from minor structural differences. Some phosphonolipids are ubiquitously distributed, while others are present almost exclusively in the layer of ciliated epithelial cells. This distinct localization of certain phosphonolipids in tissues exposed to the environment could support the hypothesis of a protective function in mollusks. This study highlights that the tissue specific distribution of an individual metabolite can be a valuable tool for inferring its function and guiding functional analyses.
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Affiliation(s)
- Patric Bourceau
- Max Planck Institute for Marine Microbiology, Bremen, Germany
- MARUM—Center for Marine Environmental Sciences of the University of Bremen, Bremen, Germany
| | - Dolma Michellod
- Max Planck Institute for Marine Microbiology, Bremen, Germany
| | - Benedikt Geier
- Max Planck Institute for Marine Microbiology, Bremen, Germany
| | - Manuel Liebeke
- Max Planck Institute for Marine Microbiology, Bremen, Germany
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31
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Wink K, van der Loh M, Hartner N, Polack M, Dusny C, Schmid A, Belder D. Quantification of Biocatalytic Transformations by Single Microbial Cells Enabled by Tailored Integration of Droplet Microfluidics and Mass Spectrometry. Angew Chem Int Ed Engl 2022; 61:e202204098. [PMID: 35511505 PMCID: PMC9401594 DOI: 10.1002/anie.202204098] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Indexed: 12/23/2022]
Abstract
Improving the performance of chemical transformations catalysed by microbial biocatalysts requires a deep understanding of cellular processes. While the cellular heterogeneity of cellular characteristics, such as the concentration of high abundant cellular content, is well studied, little is known about the reactivity of individual cells and its impact on the chemical identity, quantity, and purity of excreted products. Biocatalytic transformations were monitored chemically specific and quantifiable at the single-cell level by integrating droplet microfluidics, cell imaging, and mass spectrometry. Product formation rates for individual Saccharomyces cerevisiae cells were obtained by i) incubating nanolitre-sized droplets for product accumulation in microfluidic devices, ii) an imaging setup to determine the number of cells in the droplets, and iii) electrospray ionisation mass spectrometry for reading the chemical contents of individual droplets. These findings now enable the study of whole-cell biocatalysis at single-cell resolution.
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Affiliation(s)
- Konstantin Wink
- University of LeipzigInstitute of Analytical Chemistry04107LeipzigGermany
| | - Marie van der Loh
- University of LeipzigInstitute of Analytical Chemistry04107LeipzigGermany
| | - Nora Hartner
- University of LeipzigInstitute of Analytical Chemistry04107LeipzigGermany
| | - Matthias Polack
- University of LeipzigInstitute of Analytical Chemistry04107LeipzigGermany
| | - Christian Dusny
- Department Solar MaterialsHelmholtz Centre for Environmental Research (UFZ)04318LeipzigGermany
| | - Andreas Schmid
- Department Solar MaterialsHelmholtz Centre for Environmental Research (UFZ)04318LeipzigGermany
| | - Detlev Belder
- University of LeipzigInstitute of Analytical Chemistry04107LeipzigGermany
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32
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Källberg J, Xiao W, Van Assche D, Baret JC, Taly V. Frontiers in single cell analysis: multimodal technologies and their clinical perspectives. LAB ON A CHIP 2022; 22:2403-2422. [PMID: 35703438 DOI: 10.1039/d2lc00220e] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Single cell multimodal analysis is at the frontier of single cell research: it defines the roles and functions of distinct cell types through simultaneous analysis to provide unprecedented insight into cellular processes. Current single cell approaches are rapidly moving toward multimodal characterizations. It replaces one-dimensional single cell analysis, for example by allowing for simultaneous measurement of transcription and post-transcriptional regulation, epigenetic modifications and/or surface protein expression. By providing deeper insights into single cell processes, multimodal single cell analyses paves the way to new understandings in various cellular processes such as cell fate decisions, physiological heterogeneity or genotype-phenotype linkages. At the forefront of this, microfluidics is key for high-throughput single cell analysis. Here, we present an overview of the recent multimodal microfluidic platforms having a potential in biomedical research, with a specific focus on their potential clinical applications.
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Affiliation(s)
- Julia Källberg
- Centre de Recherche des Cordeliers, INSERM, CNRS, Université Paris Cité, Sorbonne Université, USPC, Equipe labellisée Ligue Nationale contre le cancer, Paris, France.
| | - Wenjin Xiao
- Centre de Recherche des Cordeliers, INSERM, CNRS, Université Paris Cité, Sorbonne Université, USPC, Equipe labellisée Ligue Nationale contre le cancer, Paris, France.
| | - David Van Assche
- University of Bordeaux, CNRS, Centre de Recherche Paul Pascal, UMR 5031, Pessac 33600, France.
| | - Jean-Christophe Baret
- University of Bordeaux, CNRS, Centre de Recherche Paul Pascal, UMR 5031, Pessac 33600, France.
- Institut Universitaire de France, Paris 75005, France
| | - Valerie Taly
- Centre de Recherche des Cordeliers, INSERM, CNRS, Université Paris Cité, Sorbonne Université, USPC, Equipe labellisée Ligue Nationale contre le cancer, Paris, France.
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33
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Predicting Algorithm of Tissue Cell Ratio Based on Deep Learning Using Single-Cell RNA Sequencing. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12125790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Background: Understanding the proportion of cell types in heterogeneous tissue samples is important in bioinformatics. It is a challenge to infer the proportion of tissues using bulk RNA sequencing data in bioinformatics because most traditional algorithms for predicting tissue cell ratios heavily rely on standardized specific cell-type gene expression profiles, and do not consider tissue heterogeneity. The prediction accuracy of algorithms is limited, and robustness is lacking. This means that new approaches are needed urgently. Methods: In this study, we introduced an algorithm that automatically predicts tissue cell ratios named Autoptcr. The algorithm uses the data simulated by single-cell RNA sequencing (ScRNA-Seq) for model training, using convolutional neural networks (CNNs) to extract intrinsic relationships between genes and predict the cell proportions of tissues. Results: We trained the algorithm using simulated bulk samples and made predictions using real bulk PBMC data. Comparing Autoptcr with existing advanced algorithms, the Pearson correlation coefficient between the actual value of Autoptcr and the predicted value was the highest, reaching 0.903. Tested on a bulk sample, the correlation coefficient of Lin was 41% higher than that of CSx. The algorithm can infer tissue cell proportions directly from tissue gene expression data. Conclusions: The Autoptcr algorithm uses simulated ScRNA-Seq data for training to solve the problem of specific cell-type gene expression profiles. It also has high prediction accuracy and strong noise resistance for the tissue cell ratio. This work is expected to provide new research ideas for the prediction of tissue cell proportions.
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34
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Wink K, Loh M, Hartner N, Polack M, Dusny C, Schmid A, Belder D. Quantifizierung biokatalytischer Umwandlungen durch einzelne mikrobielle Zellen mittels maßgeschneiderter Integration von Tröpfchenmikrofluidik und Massenspektrometrie. Angew Chem Int Ed Engl 2022. [DOI: 10.1002/ange.202204098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Konstantin Wink
- Universität Leipzig Institut für Analytische Chemie 04107 Leipzig Deutschland
| | - Marie Loh
- Universität Leipzig Institut für Analytische Chemie 04107 Leipzig Deutschland
| | - Nora Hartner
- Universität Leipzig Institut für Analytische Chemie 04107 Leipzig Deutschland
| | - Matthias Polack
- Universität Leipzig Institut für Analytische Chemie 04107 Leipzig Deutschland
| | - Christian Dusny
- Department Solare Materialien Helmholtz-Zentrum für Umweltforschung (UFZ) 04318 Leipzig Deutschland
| | - Andreas Schmid
- Department Solare Materialien Helmholtz-Zentrum für Umweltforschung (UFZ) 04318 Leipzig Deutschland
| | - Detlev Belder
- Universität Leipzig Institut für Analytische Chemie 04107 Leipzig Deutschland
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Abstract
Rheumatoid arthritis is an autoimmune disease that causes significant morbidity. Application of cellular profiling techniques such as single-cell transcriptomics and spatial transcriptomics has uncovered novel pathogenic cell types in RA joint tissues and revealed marked heterogeneity in the cellular composition among RA patients. Together, these insights provide exciting opportunities to translate discoveries into precision medicine in RA. The present review aims to highlight novel insights into RA pathology and discuss key steps needed to translate these discoveries into actionable changes in clinical practice. We review the efforts to identify surrogate biomarkers that could be used to predict RA synovial tissue phenotypes and the corresponding responses to therapy. Finally, we discuss the opportunity to develop novel patient-derived organoid systems as a platform for therapeutic target validation.
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Affiliation(s)
- Kartik Bhamidipati
- Department of Medicine, Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Harvard Medical School, USA.
| | - Kevin Wei
- Center for Cellular Profiling - Single Cell Multiomics Core, Brigham and Women's Hospital, Harvard Medical School, USA.
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36
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Bahnemann J, Grünberger A. Microfluidics in Biotechnology: Overview and Status Quo. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2022; 179:1-16. [DOI: 10.1007/10_2022_206] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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37
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da Silva Zandonadi F, dos Santos EAF, Marques MS, Sussulini A. Metabolomics: A Powerful Tool to Understand the Schizophrenia Biology. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1400:105-119. [DOI: 10.1007/978-3-030-97182-3_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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