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Murali R, Wanjari UR, Mukherjee AG, Gopalakrishnan AV, Kannampuzha S, Namachivayam A, Madhyastha H, Renu K, Ganesan R. Crosstalk between COVID-19 Infection and Kidney Diseases: A Review on the Metabolomic Approaches. Vaccines (Basel) 2023; 11:vaccines11020489. [PMID: 36851366 PMCID: PMC9959335 DOI: 10.3390/vaccines11020489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 02/16/2023] [Accepted: 02/17/2023] [Indexed: 02/22/2023] Open
Abstract
The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a respiratory disorder. Various organ injuries have been reported in response to this virus, including kidney injury and, in particular, kidney tubular injury. It has been discovered that infection with the virus does not only cause new kidney disease but also increases treatment difficulty and mortality rates in people with kidney diseases. In individuals hospitalized with COVID-19, urinary metabolites from several metabolic pathways are used to distinguish between patients with acute kidney injury (AKI) and those without. This review summarizes the pathogenesis, pathophysiology, treatment strategies, and role of metabolomics in relation to AKI in COVID-19 patients. Metabolomics is likely to play a greater role in predicting outcomes for patients with kidney disease and COVID-19 with varying levels of severity in the near future as data on metabolic profiles expand rapidly. Here, we also discuss the correlation between COVID-19 and kidney diseases and the available metabolomics approaches.
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Affiliation(s)
- Reshma Murali
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, Tamil Nadu, India
| | - Uddesh Ramesh Wanjari
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, Tamil Nadu, India
| | - Anirban Goutam Mukherjee
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, Tamil Nadu, India
| | - Abilash Valsala Gopalakrishnan
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, Tamil Nadu, India
- Correspondence: (A.V.G.); (R.G.)
| | - Sandra Kannampuzha
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, Tamil Nadu, India
| | - Arunraj Namachivayam
- Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, Tamil Nadu, India
| | - Harishkumar Madhyastha
- Department of Cardiovascular Physiology, Faculty of Medicine, University of Miyazaki, Miyazaki 889-1692, Japan
| | - Kaviyarasi Renu
- Center of Molecular Medicine and Diagnostics (COMMAND), Department of Biochemistry, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 600077, Tamil Nadu, India
| | - Raja Ganesan
- Institute for Liver and Digestive Diseases, College of Medicine, Hallym University, Chuncheon 24252, Republic of Korea
- Correspondence: (A.V.G.); (R.G.)
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2
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Palermo A. Metabolomics- and systems-biology-guided discovery of metabolite lead compounds and druggable targets. Drug Discov Today 2023; 28:103460. [PMID: 36427778 DOI: 10.1016/j.drudis.2022.103460] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/16/2022] [Accepted: 11/21/2022] [Indexed: 11/27/2022]
Abstract
Metabolomics enables the comprehensive and unbiased analysis of metabolites and lipids in biological systems. In conjunction with high-throughput activity screening, big data and synthetic biology, metabolomics can guide the discovery of lead compounds with pharmacological activity from natural sources and the gut microbiome. In combination with other omics, metabolomics can further unlock the elucidation of compound toxicity, the mode of action and novel druggable targets of disease. Here, we discuss the workflows, limitations and future opportunities to leverage metabolomics and big data in conjunction with systems and synthetic biology for streamlining the discovery and development of molecules of pharmaceutical interest.
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Affiliation(s)
- Amelia Palermo
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, UCLA, Los Angeles, CA 90095, USA.
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3
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Deng K, Wang X, Ing N, Opgenorth P, de Raad M, Kim J, Simmons BA, Adams PD, Singh AK, Lee TS, Northen TR. Rapid quantification of alcohol production in microorganisms based on nanostructure-initiator mass spectrometry (NIMS). Anal Biochem 2023; 662:114997. [PMID: 36435200 DOI: 10.1016/j.ab.2022.114997] [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: 07/28/2022] [Revised: 11/17/2022] [Accepted: 11/18/2022] [Indexed: 11/25/2022]
Abstract
We described a mass spectrometry-based assay to rapidly quantify the production of primary alcohols directly from cell cultures. This novel assay used the combination of TEMPO-based oxidation chemistry and oxime ligation, followed by product analysis based on Nanostructure-Initiator Mass Spectrometry. This assay enables quantitative monitor both C5 to C18 alcohols as well as glucose and gluconate in the growth medium to support strain characterization and optimization. We find that this assay yields similar results to gas chromatography for isoprenol production but required much less acquisition time per sample. We applied this assay to gain new insights into P. Putida's utilization of alcohols and find that this strain largely could not grow on heptanol and octanol.
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Affiliation(s)
- Kai Deng
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Sandia National Laboratories, Livermore, CA, 94551, USA.
| | - Xi Wang
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Nicole Ing
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Sandia National Laboratories, Livermore, CA, 94551, USA
| | - Paul Opgenorth
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Markus de Raad
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Jinho Kim
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Blake A Simmons
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Paul D Adams
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA; University of California, Berkeley, CA, 94720, USA
| | - Anup K Singh
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Lawrence Livermore National Laboratory, Livermore, 94550, USA
| | - Taek Soon Lee
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Trent R Northen
- Joint BioEnergy Institute, Emeryville, CA, 94608, USA; Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
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4
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Harvey DJ. Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020. MASS SPECTROMETRY REVIEWS 2022:e21806. [PMID: 36468275 DOI: 10.1002/mas.21806] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.
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Affiliation(s)
- David J Harvey
- Nuffield Department of Medicine, Target Discovery Institute, University of Oxford, Oxford, UK
- Department of Chemistry, University of Oxford, Oxford, Oxfordshire, United Kingdom
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5
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Müller WH, Verdin A, De Pauw E, Malherbe C, Eppe G. Surface-assisted laser desorption/ionization mass spectrometry imaging: A review. MASS SPECTROMETRY REVIEWS 2022; 41:373-420. [PMID: 33174287 PMCID: PMC9292874 DOI: 10.1002/mas.21670] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 10/22/2020] [Accepted: 10/24/2020] [Indexed: 05/04/2023]
Abstract
In the last decades, surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS) has attracted increasing interest due to its unique capabilities, achievable through the nanostructured substrates used to promote the analyte desorption/ionization. While the most widely recognized asset of SALDI-MS is the untargeted analysis of small molecules, this technique also offers the possibility of targeted approaches. In particular, the implementation of SALDI-MS imaging (SALDI-MSI), which is the focus of this review, opens up new opportunities. After a brief discussion of the nomenclature and the fundamental mechanisms associated with this technique, which are still highly controversial, the analytical strategies to perform SALDI-MSI are extensively discussed. Emphasis is placed on the sample preparation but also on the selection of the nanosubstrate (in terms of chemical composition and morphology) as well as its functionalization possibilities for the selective analysis of specific compounds in targeted approaches. Subsequently, some selected applications of SALDI-MSI in various fields (i.e., biomedical, biological, environmental, and forensic) are presented. The strengths and the remaining limitations of SALDI-MSI are finally summarized in the conclusion and some perspectives of this technique, which has a bright future, are proposed in this section.
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Affiliation(s)
- Wendy H. Müller
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Alexandre Verdin
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Edwin De Pauw
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Cedric Malherbe
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
| | - Gauthier Eppe
- Mass Spectrometry Laboratory, MolSys Research Unit, Chemistry DepartmentUniversity of LiègeLiègeBelgium
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6
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Palermo A. Mass Spectrometry Imaging of Metabolites by Nanostructure Initiator Mass Spectrometry with Fluorinated Gold Nanoparticles. Methods Mol Biol 2022; 2437:117-125. [PMID: 34902144 DOI: 10.1007/978-1-0716-2030-4_8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Nanostructure initiator mass spectrometry (NIMS) with fluorinated gold nanoparticles (f-AuNPs) enables the detection and spatial localization of a breath of polar metabolites and lipids with high spatial resolution and ultrasensitivity. Here we describe the methods and procedures for the synthesis and application of f-AuNPs for NIMS of small molecule metabolites and lipids in biological tissues, encompassing sample preparation, mass spectrometric detection, and data analysis and interpretation.
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Affiliation(s)
- Amelia Palermo
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA, USA.
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7
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Müller WH, De Pauw E, Far J, Malherbe C, Eppe G. Imaging lipids in biological samples with surface-assisted laser desorption/ionization mass spectrometry: A concise review of the last decade. Prog Lipid Res 2021; 83:101114. [PMID: 34217733 DOI: 10.1016/j.plipres.2021.101114] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 06/25/2021] [Accepted: 06/29/2021] [Indexed: 02/06/2023]
Abstract
Knowing the spatial location of the lipid species present in biological samples is of paramount importance for the elucidation of pathological and physiological processes. In this context, mass spectrometry imaging (MSI) has emerged as a powerful technology allowing the visualization of the spatial distributions of biomolecules, including lipids, in complex biological samples. Among the different ionization methods available, the emerging surface-assisted laser desorption/ionization (SALDI) MSI offers unique capabilities for the study of lipids. This review describes the specific advantages of SALDI-MSI for lipid analysis, including the ability to perform analyses in both ionization modes with the same nanosubstrate, the detection of lipids characterized by low ionization efficiency in MALDI-MS, and the possibilities of surface modification to improve the detection of lipids. The complementarity of SALDI and MALDI-MSI is also discussed. Finally, this review presents data processing strategies applied in SALDI-MSI of lipids, as well as examples of applications of SALDI-MSI in biomedical lipidomics.
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Affiliation(s)
- Wendy H Müller
- Mass Spectrometry Laboratory, MolSys RU, Department of Chemistry, University of Liège, Allée du Six Août, 11 - Quartier Agora, 4000 Liège, Belgium
| | - Edwin De Pauw
- Mass Spectrometry Laboratory, MolSys RU, Department of Chemistry, University of Liège, Allée du Six Août, 11 - Quartier Agora, 4000 Liège, Belgium
| | - Johann Far
- Mass Spectrometry Laboratory, MolSys RU, Department of Chemistry, University of Liège, Allée du Six Août, 11 - Quartier Agora, 4000 Liège, Belgium
| | - Cedric Malherbe
- Mass Spectrometry Laboratory, MolSys RU, Department of Chemistry, University of Liège, Allée du Six Août, 11 - Quartier Agora, 4000 Liège, Belgium
| | - Gauthier Eppe
- Mass Spectrometry Laboratory, MolSys RU, Department of Chemistry, University of Liège, Allée du Six Août, 11 - Quartier Agora, 4000 Liège, Belgium.
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8
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Borges R, Colby SM, Das S, Edison AS, Fiehn O, Kind T, Lee J, Merrill AT, Merz KM, Metz TO, Nunez JR, Tantillo DJ, Wang LP, Wang S, Renslow RS. Quantum Chemistry Calculations for Metabolomics. Chem Rev 2021; 121:5633-5670. [PMID: 33979149 PMCID: PMC8161423 DOI: 10.1021/acs.chemrev.0c00901] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Indexed: 02/07/2023]
Abstract
A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.
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Affiliation(s)
- Ricardo
M. Borges
- Walter
Mors Institute of Research on Natural Products, Federal University of Rio de Janeiro, Rio de Janeiro 21941-901, Brazil
| | - Sean M. Colby
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Susanta Das
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Arthur S. Edison
- Departments
of Genetics and Biochemistry and Molecular Biology, Complex Carbohydrate
Research Center and Institute of Bioinformatics, University of Georgia, Athens, Georgia 30602, United States
| | - Oliver Fiehn
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
| | - Tobias Kind
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
| | - Jesi Lee
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Amy T. Merrill
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Kenneth M. Merz
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Thomas O. Metz
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Jamie R. Nunez
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Dean J. Tantillo
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Lee-Ping Wang
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Shunyang Wang
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Ryan S. Renslow
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
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