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Zhan L, Huang Y, Wang G. Multi-modal mass spectrometry imaging of a single tissue section. JOURNAL OF MASS SPECTROMETRY : JMS 2024; 59:e5074. [PMID: 39017393 DOI: 10.1002/jms.5074] [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: 02/08/2024] [Revised: 06/10/2024] [Accepted: 06/21/2024] [Indexed: 07/18/2024]
Abstract
Mass spectrometry imaging (MSI) was developed to visualize spatial chemical information within tissues, thereby facilitating spatial multi-omic analysis. However, due to the limited spatial information provided by individual modal MSI, correlating various chemical data within tissues remains a significant challenge. In recent years, multimodal MSI has garnered considerable attention due to its ability to visualize the spatial distributions of multiple biomolecules within tissues. Among the strategies employed in this field, multimodal imaging on a single tissue section circumvents multiple issues introduced by integration of images of consecutive tissue sections. In this minireview, we provide an overview of multimodal MSI on a single tissue section, with a particular focus on the use of Matrix-Assisted Laser Desorption/Ionization-MSI for spatial multi-omic investigations that offer a comprehensive and in-depth elucidation of the biological state and activities, aiming to inspire the development of new approaches in this field.
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Affiliation(s)
- Lingpeng Zhan
- Institute of Chemical Biology, Shenzhen Bay Laboratory, Shenzhen, China
| | - Yanyi Huang
- Institute of Chemical Biology, Shenzhen Bay Laboratory, Shenzhen, China
- Biomedical Pioneering Innovation Center, Peking University, Beijing, China
- College of Chemistry and Molecular Engineering, Beijing National Laboratory for Molecular Sciences, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Guanbo Wang
- Institute of Chemical Biology, Shenzhen Bay Laboratory, Shenzhen, China
- Biomedical Pioneering Innovation Center, Peking University, Beijing, China
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2
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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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3
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Kasri A, Camporesi E, Gkanatsiou E, Boluda S, Brinkmalm G, Stimmer L, Ge J, Hanrieder J, Villain N, Duyckaerts C, Vermeiren Y, Pape SE, Nicolas G, Laquerrière A, De Deyn PP, Wallon D, Blennow K, Strydom A, Zetterberg H, Potier MC. Amyloid-β peptide signature associated with cerebral amyloid angiopathy in familial Alzheimer's disease with APPdup and Down syndrome. Acta Neuropathol 2024; 148:8. [PMID: 39026031 PMCID: PMC11258176 DOI: 10.1007/s00401-024-02756-4] [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: 02/02/2024] [Revised: 06/11/2024] [Accepted: 06/11/2024] [Indexed: 07/20/2024]
Abstract
Alzheimer's disease (AD) is characterized by extracellular amyloid plaques containing amyloid-β (Aβ) peptides, intraneuronal neurofibrillary tangles, extracellular neuropil threads, and dystrophic neurites surrounding plaques composed of hyperphosphorylated tau protein (pTau). Aβ can also deposit in blood vessel walls leading to cerebral amyloid angiopathy (CAA). While amyloid plaques in AD brains are constant, CAA varies among cases. The study focuses on differences observed between rare and poorly studied patient groups with APP duplications (APPdup) and Down syndrome (DS) reported to have higher frequencies of elevated CAA levels in comparison to sporadic AD (sAD), most of APP mutations, and controls. We compared Aβ and tau pathologies in postmortem brain tissues across cases and Aβ peptides using mass spectrometry (MS). We further characterized the spatial distribution of Aβ peptides with MS-brain imaging. While intraparenchymal Aβ deposits were numerous in sAD, DS with AD (DS-AD) and AD with APP mutations, these were less abundant in APPdup. On the contrary, Aβ deposits in the blood vessels were abundant in APPdup and DS-AD while only APPdup cases displayed high Aβ deposits in capillaries. Investigation of Aβ peptide profiles showed a specific increase in Aβx-37, Aβx-38 and Aβx-40 but not Aβx-42 in APPdup cases and to a lower extent in DS-AD cases. Interestingly, N-truncated Aβ2-x peptides were particularly increased in APPdup compared to all other groups. This result was confirmed by MS-imaging of leptomeningeal and parenchymal vessels from an APPdup case, suggesting that CAA is associated with accumulation of shorter Aβ peptides truncated both at N- and C-termini in blood vessels. Altogether, this study identified striking differences in the localization and composition of Aβ deposits between AD cases, particularly APPdup and DS-AD, both carrying three genomic copies of the APP gene. Detection of specific Aβ peptides in CSF or plasma of these patients could improve the diagnosis of CAA and their inclusion in anti-amyloid immunotherapy treatments.
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Affiliation(s)
- Amal Kasri
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, APHP, Hôpital de La Pitié Salpêtrière, InsermParis, France
| | - Elena Camporesi
- Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Eleni Gkanatsiou
- Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Susana Boluda
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, APHP, Hôpital de La Pitié Salpêtrière, InsermParis, France
- Department of Neuropathology Raymond Escourolle, AP-HP, Pitié-Salpêtrière University Hospital, Paris, France
| | - Gunnar Brinkmalm
- Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Lev Stimmer
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, APHP, Hôpital de La Pitié Salpêtrière, InsermParis, France
| | - Junyue Ge
- Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Jörg Hanrieder
- Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK
| | - Nicolas Villain
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, APHP, Hôpital de La Pitié Salpêtrière, InsermParis, France
| | - Charles Duyckaerts
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, APHP, Hôpital de La Pitié Salpêtrière, InsermParis, France
- Department of Neuropathology Raymond Escourolle, AP-HP, Pitié-Salpêtrière University Hospital, Paris, France
| | - Yannick Vermeiren
- Department of Biomedical Sciences, Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- Division of Human Nutrition and Health, Chair Group Nutritional Biology, Wageningen University and Research (WUR), Wageningen, The Netherlands
| | - Sarah E Pape
- Institute of Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, UK
| | - Gaël Nicolas
- Department of Genetics, CNRMAJ, Univ Rouen Normandie, Normandie Univ, Inserm U1245 and CHU Rouen, F-76000, Rouen, France
| | - Annie Laquerrière
- Department of Pathology, Univ Rouen Normandie, Normandie Univ, Inserm U1245 and CHU Rouen, F-76000, Rouen, France
| | - Peter Paul De Deyn
- Department of Biomedical Sciences, Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Alzheimer Center, University of Groningen, University Medical Center Groningen (UMCG), Groningen, The Netherlands
| | - David Wallon
- Department of Neurology, CNRMAJ, Univ Rouen Normandie, Normandie Univ, Inserm U1245 and CHU Rouen, 76000, Rouen, France
| | - Kaj Blennow
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, APHP, Hôpital de La Pitié Salpêtrière, InsermParis, France
- Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, Department of Neurology, Institute On Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, People's Republic of China
| | - Andre Strydom
- Institute of Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, UK
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.
- Department of Neurology and Alzheimer Center, University of Groningen, University Medical Center Groningen (UMCG), Groningen, The Netherlands.
- UK Dementia Research Institute at UCL, London, UK.
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China.
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, University of Wisconsin-Madison, Madison, WI, USA.
| | - Marie-Claude Potier
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, APHP, Hôpital de La Pitié Salpêtrière, InsermParis, France.
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Mardanyan S, Sharoyan S, Antonyan A. Diversity of amyloid beta peptide actions. Rev Neurosci 2024; 35:387-398. [PMID: 38281140 DOI: 10.1515/revneuro-2023-0100] [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: 08/30/2023] [Accepted: 12/16/2023] [Indexed: 01/30/2024]
Abstract
Fibril formation by amyloidogenic proteins and peptides is considered the cause of a number of incurable diseases. One of the most known amyloid diseases is Alzheimer's disease (AD). Traditionally, amyloidogenic beta peptides Aβ40 and Aβ42 (Aβs) are considered as main causes of AD and the foremost targets in AD fight. The main efforts in pharmacology are aimed at reducing Aβs concentration to prevent their accumulation, aggregation, formation of senile plaques, neuronal death, and neurodegeneration. However, a number of publications have demonstrated certain beneficial physiological effects of Aβs. Simultaneously, it is indicated that the effects of Aβs turn into pathological due to the development of certain diseases in the body. The accumulation of C- and N-terminal truncated Aβs under diverse conditions is supposed to play a role in AD development. The significance of transformation of glutamate residue at positions 3 or 11 of Aβs catalyzed by glutaminyl cyclase making them more degradation resistant, hydrophobic, and prone to aggregation, as well as the participation of dipeptidyl peptidase IV in these transformations are discussed. The experimental data presented confirm the maintenance of physiological, nonaggregated state of Aβs by plant preparations. In conclusion, this review suggests that in the fight against AD, instead of removing Aβs, preference should be given to the treatment of common diseases. Glutaminyl cyclase and dipeptidyl peptidase IV can be considered as targets in AD treatment. Flavonoids and plant preparations that possess antiamyloidogenic propensity are proposed as beneficial neuroprotective, anticancer, and antidiabetic food additives.
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Affiliation(s)
- Sona Mardanyan
- H. Buniatian Institute of Biochemistry of Armenian National Academy of Sciences, Yerevan 0014, Republic of Armenia
| | - Svetlana Sharoyan
- H. Buniatian Institute of Biochemistry of Armenian National Academy of Sciences, Yerevan 0014, Republic of Armenia
| | - Alvard Antonyan
- H. Buniatian Institute of Biochemistry of Armenian National Academy of Sciences, Yerevan 0014, Republic of Armenia
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Cheng H, Miller D, Southwell N, Fischer JL, Taylor I, Salbaum JM, Kappen C, Hu F, Yang C, Gross SS, D'Aurelio M, Chen Q. Untargeted Pixel-by-Pixel Imaging of Metabolite Ratio Pairs as a Novel Tool for Biomedical Discovery in Mass Spectrometry Imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.10.575105. [PMID: 38370710 PMCID: PMC10871215 DOI: 10.1101/2024.01.10.575105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Mass spectrometry imaging (MSI) is a powerful technology used to define the spatial distribution and relative abundance of structurally identified and yet-undefined metabolites across tissue cryosections. While numerous software packages enable pixel-by-pixel imaging of individual metabolites, the research community lacks a discovery tool that images all metabolite abundance ratio pairs. Importantly, recognition of correlated metabolite pairs informs discovery of unanticipated molecules contributing to shared metabolic pathways, uncovers hidden metabolic heterogeneity across cells and tissue subregions, and indicates single-timepoint flux through pathways of interest. Here, we describe the development and implementation of an untargeted R package workflow for pixel-by-pixel ratio imaging of all metabolites detected in an MSI experiment. Considering untargeted MSI studies of murine brain and embryogenesis, we demonstrate that ratio imaging minimizes systematic data variation introduced by sample handling and instrument drift, markedly enhances spatial image resolution, and reveals previously unrecognized metabotype-distinct tissue regions. Furthermore, ratio imaging facilitates identification of novel regional biomarkers and provides anatomical information regarding spatial distribution of metabolite-linked biochemical pathways. The algorithm described herein is applicable to any MSI dataset containing spatial information for metabolites, peptides or proteins, offering a potent tool to enhance knowledge obtained from current spatial metabolite profiling technologies.
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6
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Prentice BM. Imaging with mass spectrometry: Which ionization technique is best? JOURNAL OF MASS SPECTROMETRY : JMS 2024; 59:e5016. [PMID: 38625003 DOI: 10.1002/jms.5016] [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: 01/12/2024] [Revised: 02/07/2024] [Accepted: 02/21/2024] [Indexed: 04/17/2024]
Abstract
The use of mass spectrometry (MS) to acquire molecular images of biological tissues and other substrates has developed into an indispensable analytical tool over the past 25 years. Imaging mass spectrometry technologies are widely used today to study the in situ spatial distributions for a variety of analytes. Early MS images were acquired using secondary ion mass spectrometry and matrix-assisted laser desorption/ionization. Researchers have also designed and developed other ionization techniques in recent years to probe surfaces and generate MS images, including desorption electrospray ionization (DESI), nanoDESI, laser ablation electrospray ionization, and infrared matrix-assisted laser desorption electrospray ionization. Investigators now have a plethora of ionization techniques to select from when performing imaging mass spectrometry experiments. This brief perspective will highlight the utility and relative figures of merit of these techniques within the context of their use in imaging mass spectrometry.
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Affiliation(s)
- Boone M Prentice
- Department of Chemistry, University of Florida, Gainesville, Florida, USA
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Cartas-Cejudo P, Cortés A, Lachén-Montes M, Anaya-Cubero E, Peral E, Ausín K, Díaz-Peña R, Fernández-Irigoyen J, Santamaría E. Mapping the human brain proteome: opportunities, challenges, and clinical potential. Expert Rev Proteomics 2024; 21:55-63. [PMID: 38299555 DOI: 10.1080/14789450.2024.2313073] [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] [Accepted: 01/24/2024] [Indexed: 02/02/2024]
Abstract
INTRODUCTION Due to the segmented functions and complexity of the human brain, the characterization of molecular profiles within specific areas such as brain structures and biofluids is essential to unveil the molecular basis for structure specialization as well as the molecular imbalance associated with neurodegenerative and psychiatric diseases. AREAS COVERED Much of our knowledge about brain functionality derives from neurophysiological, anatomical, and transcriptomic approaches. More recently, laser capture and imaging proteomics, technological and computational developments in LC-MS/MS, as well as antibody/aptamer-based platforms have allowed the generation of novel cellular, spatial, and posttranslational dimensions as well as innovative facets in biomarker validation and druggable target identification. EXPERT OPINION Proteomics is a powerful toolbox to functionally characterize, quantify, and localize the extensive protein catalog of the human brain across physiological and pathological states. Brain function depends on multi-dimensional protein homeostasis, and its elucidation will help us to characterize biological pathways that are essential to properly maintain cognitive functions. In addition, comprehensive human brain pathological proteomes may be the basis in computational drug-repositioning methods as a strategy for unveiling potential new therapies in neurodegenerative and psychiatric disorders.
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Affiliation(s)
- Paz Cartas-Cejudo
- Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Adriana Cortés
- Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Mercedes Lachén-Montes
- Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Elena Anaya-Cubero
- Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Erika Peral
- Proteomics Platform, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Karina Ausín
- Proteomics Platform, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Ramón Díaz-Peña
- Proteomics Platform, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Joaquín Fernández-Irigoyen
- Proteomics Platform, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Enrique Santamaría
- Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
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Wang Z, Zhu H, Xiong W. Advances in mass spectrometry-based multi-scale metabolomic methodologies and their applications in biological and clinical investigations. Sci Bull (Beijing) 2023; 68:2268-2284. [PMID: 37666722 DOI: 10.1016/j.scib.2023.08.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/25/2023] [Accepted: 08/22/2023] [Indexed: 09/06/2023]
Abstract
Metabolomics is a nascent field of inquiry that emerged in the late 20th century. It encompasses the comprehensive profiling of metabolites across a spectrum of organisms, ranging from bacteria and cells to tissues. The rapid evolution of analytical methods and data analysis has greatly accelerated progress in this dynamic discipline over recent decades. Sophisticated techniques such as liquid chromatograph mass spectrometry (MS), gas chromatograph MS, capillary electrophoresis MS, and nuclear magnetic resonance serve as the cornerstone of metabolomic analysis. Building upon these methods, a plethora of modifications and combinations have emerged to propel the advancement of metabolomics. Despite this progress, scrutinizing metabolism at the single-cell or single-organelle level remains an arduous task over the decades. Some of the most thrilling advancements, such as single-cell and single-organelle metabolic profiling techniques, offer profound insights into the intricate mechanisms within cells and organelles. This allows for a comprehensive study of metabolic heterogeneity and its pivotal role in multiple biological processes. The progress made in MS imaging has enabled high-resolution in situ metabolic profiling of tissue sections and even individual cells. Spatial reconstruction techniques enable the direct representation of metabolic distribution and alteration in three-dimensional space. The application of novel metabolomic techniques has led to significant breakthroughs in biological and clinical studies, including the discovery of novel metabolic pathways, determination of cell fate in differentiation, anti-aging intervention through modulating metabolism, metabolomics-based clinicopathologic analysis, and surgical decision-making based on on-site intraoperative metabolic analysis. This review presents a comprehensive overview of both conventional and innovative metabolomic techniques, highlighting their applications in groundbreaking biological and clinical studies.
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Affiliation(s)
- Ziyi Wang
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Hefei National Research Center for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China
| | - Hongying Zhu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Hefei National Research Center for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China; Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing, Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; CAS Key Laboratory of Brain Function and Disease, Hefei 230026, China; Anhui Province Key Laboratory of Biomedical Aging Research, Hefei 230026, China.
| | - Wei Xiong
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Hefei National Research Center for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China; Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing, Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; CAS Key Laboratory of Brain Function and Disease, Hefei 230026, China; Anhui Province Key Laboratory of Biomedical Aging Research, Hefei 230026, China.
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