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Chen HJ, Sévin DC, Griffith GR, Vappiani J, Booty LM, van Roomen CPAA, Kuiper J, Dunnen JD, de Jonge WJ, Prinjha RK, Mander PK, Grandi P, Wyspianska BS, de Winther MPJ. Integrated metabolic-transcriptomic network identifies immunometabolic modulations in human macrophages. Cell Rep 2024; 43:114741. [PMID: 39276347 DOI: 10.1016/j.celrep.2024.114741] [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: 11/23/2023] [Revised: 06/08/2024] [Accepted: 08/26/2024] [Indexed: 09/17/2024] Open
Abstract
Macrophages exhibit diverse phenotypes and respond flexibly to environmental cues through metabolic remodeling. In this study, we present a comprehensive multi-omics dataset integrating intra- and extracellular metabolomes with transcriptomic data to investigate the metabolic impact on human macrophage function. Our analysis establishes a metabolite-gene correlation network that characterizes macrophage activation. We find that the concurrent inhibition of tryptophan catabolism by IDO1 and IL4I1 inhibitors suppresses the macrophage pro-inflammatory response, whereas single inhibition leads to pro-inflammatory activation. We find that a subset of anti-inflammatory macrophages activated by Fc receptor signaling promotes glycolysis, challenging the conventional concept of reduced glycolysis preference in anti-inflammatory macrophages. We demonstrate that cholesterol accumulation suppresses macrophage IFN-γ responses. Our integrated network enables the discovery of immunometabolic features, provides insights into macrophage functional metabolic reprogramming, and offers valuable resources for researchers exploring macrophage immunometabolic characteristics and potential therapeutic targets for immune-related disorders.
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Affiliation(s)
- Hung-Jen Chen
- Department of Medical Biochemistry, Experimental Vascular Biology, Atherosclerosis and Ischemic Syndromes, Amsterdam Cardiovascular Sciences, Amsterdam Institute for Immunology and Infectious Diseases, Amsterdam University Medical Center, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands
| | | | - Guillermo R Griffith
- Department of Medical Biochemistry, Experimental Vascular Biology, Atherosclerosis and Ischemic Syndromes, Amsterdam Cardiovascular Sciences, Amsterdam Institute for Immunology and Infectious Diseases, Amsterdam University Medical Center, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands
| | | | - Lee M Booty
- Immunology Network, Immunology Research Unit, GSK, SG1 2NY Stevenage, UK
| | - Cindy P A A van Roomen
- Department of Medical Biochemistry, Experimental Vascular Biology, Atherosclerosis and Ischemic Syndromes, Amsterdam Cardiovascular Sciences, Amsterdam Institute for Immunology and Infectious Diseases, Amsterdam University Medical Center, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands
| | - Johan Kuiper
- Division of BioTherapeutics, Leiden Academic Centre for Drug Research, 2333 CL Leiden, the Netherlands
| | - Jeroen den Dunnen
- Center for Experimental and Molecular Medicine, Amsterdam Institute for Immunology and Infectious Diseases, Amsterdam University Medical Center, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands
| | - Wouter J de Jonge
- Tytgat Institute for Liver and Intestinal Research, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam University Medical Center, Location AMC, University of Amsterdam, 1105 BK Amsterdam, the Netherlands
| | - Rab K Prinjha
- Immunology Research Unit, GSK Medicines Research Centre, SG1 2NY Stevenage, UK
| | - Palwinder K Mander
- Immunology Research Unit, GSK Medicines Research Centre, SG1 2NY Stevenage, UK
| | | | - Beata S Wyspianska
- Immunology Research Unit, GSK Medicines Research Centre, SG1 2NY Stevenage, UK
| | - Menno P J de Winther
- Department of Medical Biochemistry, Experimental Vascular Biology, Atherosclerosis and Ischemic Syndromes, Amsterdam Cardiovascular Sciences, Amsterdam Institute for Immunology and Infectious Diseases, Amsterdam University Medical Center, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands.
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2
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Pakkir Shah AK, Walter A, Ottosson F, Russo F, Navarro-Diaz M, Boldt J, Kalinski JCJ, Kontou EE, Elofson J, Polyzois A, González-Marín C, Farrell S, Aggerbeck MR, Pruksatrakul T, Chan N, Wang Y, Pöchhacker M, Brungs C, Cámara B, Caraballo-Rodríguez AM, Cumsille A, de Oliveira F, Dührkop K, El Abiead Y, Geibel C, Graves LG, Hansen M, Heuckeroth S, Knoblauch S, Kostenko A, Kuijpers MCM, Mildau K, Papadopoulos Lambidis S, Portal Gomes PW, Schramm T, Steuer-Lodd K, Stincone P, Tayyab S, Vitale GA, Wagner BC, Xing S, Yazzie MT, Zuffa S, de Kruijff M, Beemelmanns C, Link H, Mayer C, van der Hooft JJJ, Damiani T, Pluskal T, Dorrestein P, Stanstrup J, Schmid R, Wang M, Aron A, Ernst M, Petras D. Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data. Nat Protoc 2024:10.1038/s41596-024-01046-3. [PMID: 39304763 DOI: 10.1038/s41596-024-01046-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 07/02/2024] [Indexed: 09/22/2024]
Abstract
Feature-based molecular networking (FBMN) is a popular analysis approach for liquid chromatography-tandem mass spectrometry-based non-targeted metabolomics data. While processing liquid chromatography-tandem mass spectrometry data through FBMN is fairly streamlined, downstream data handling and statistical interrogation are often a key bottleneck. Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices. Here we provide a comprehensive guide for the statistical analysis of FBMN results, focusing on the downstream analysis of the FBMN output table. We explain the data structure and principles of data cleanup and normalization, as well as uni- and multivariate statistical analysis of FBMN results. We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. All code is shared in the form of Jupyter Notebooks ( https://github.com/Functional-Metabolomics-Lab/FBMN-STATS ). Additionally, the protocol is accompanied by a web application with a graphical user interface ( https://fbmn-statsguide.gnps2.org/ ) to lower the barrier of entry for new users and for educational purposes. Finally, we also show users how to integrate their statistical results into the molecular network using the Cytoscape visualization tool. Throughout the protocol, we use a previously published environmental metabolomics dataset for demonstration purposes. Together, the protocol, code and web application provide a complete guide and toolbox for FBMN data integration, cleanup and advanced statistical analysis, enabling new users to uncover molecular insights from their non-targeted metabolomics data. Our protocol is tailored for the seamless analysis of FBMN results from Global Natural Products Social Molecular Networking and can be easily adapted to other mass spectrometry feature detection, annotation and networking tools.
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Affiliation(s)
- Abzer K Pakkir Shah
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
| | - Axel Walter
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
- Applied Bioinformatics, Department of Computer Science, University of Tübingen, Tübingen, Germany
| | - Filip Ottosson
- Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen S, Denmark
| | - Francesco Russo
- Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen S, Denmark
| | - Marcelo Navarro-Diaz
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
| | - Judith Boldt
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany
- German Center for Infection Research, Partner Site Braunschweig-Hannover, Braunschweig, Germany
| | - Jarmo-Charles J Kalinski
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Department of Biochemistry and Microbiology, Rhodes University, Makhanda, South Africa
| | - Eftychia Eva Kontou
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- The Novo Nordisk Foundation for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
| | - James Elofson
- Department of Chemistry and Biochemistry, University of Denver, Denver, CO, USA
| | - Alexandros Polyzois
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA
| | - Carolina González-Marín
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Universidad EAFIT, Medellín, Antioquia, Colombia
| | - Shane Farrell
- Bigelow Laboratory for Ocean Sciences, East Boothbay, ME, USA
- School of Marine Sciences, Darling Marine Center, University of Maine, Walpole, ME, USA
| | - Marie R Aggerbeck
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Department of Environmental Science, Aarhus University, Roskilde, Denmark
| | - Thapanee Pruksatrakul
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Thailand Science Park, Pathum Thani, Thailand
| | - Nathan Chan
- Department of Computer Science, University of California Riverside, Riverside, CA, USA
| | - Yunshu Wang
- Department of Computer Science, University of California Riverside, Riverside, CA, USA
| | - Magdalena Pöchhacker
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Department of Food Chemistry and Toxicology, University of Vienna, Vienna, Austria
| | - Corinna Brungs
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
| | - Beatriz Cámara
- Laboratorio de Microbiología Molecular y Biotecnología Ambiental, Centro de Biotecnología DAL, Universidad Técnica Federico Santa María, Valparaíso, Chile
| | | | - Andres Cumsille
- Laboratorio de Microbiología Molecular y Biotecnología Ambiental, Centro de Biotecnología DAL, Universidad Técnica Federico Santa María, Valparaíso, Chile
| | - Fernanda de Oliveira
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
- Department of Biotechnology, Engineering School of Lorena, University of São Paulo, Lorena, São Paulo, Brazil
| | - Kai Dührkop
- Department of Bioinformatics, University of Jena, Jena, Germany
| | - Yasin El Abiead
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
| | - Christian Geibel
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
| | - Lana G Graves
- Department of Environmental Systems Analysis, University of Tübingen, Tübingen, Germany
- Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany
| | - Martin Hansen
- Department of Environmental Science, Aarhus University, Roskilde, Denmark
| | - Steffen Heuckeroth
- Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany
| | - Simon Knoblauch
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
| | - Anastasiia Kostenko
- Department of Chemistry and Biochemistry, University of Denver, Denver, CO, USA
| | - Mirte C M Kuijpers
- Department of Ecology, Behavior and Evolution, University of California San Diego, San Diego, CA, USA
| | - Kevin Mildau
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Department of Analytical Chemistry, University of Vienna, Vienna, Austria
- Bioinformatics Group, Wageningen University and Research, Wageningen, the Netherlands
| | | | - Paulo Wender Portal Gomes
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
| | - Tilman Schramm
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
- Department of Biochemistry, University of California Riverside, Riverside, CA, USA
| | - Karoline Steuer-Lodd
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
- Department of Biochemistry, University of California Riverside, Riverside, CA, USA
| | - Paolo Stincone
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
| | - Sibgha Tayyab
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
| | - Giovanni Andrea Vitale
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
| | - Berenike C Wagner
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
| | - Shipei Xing
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
| | - Marquis T Yazzie
- Department of Chemistry and Biochemistry, University of Denver, Denver, CO, USA
| | - Simone Zuffa
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
| | - Martinus de Kruijff
- Helmholtz Institute for Pharmaceutical Research Saarland, Helmholtz Centre for Infection Research, Saarbrücken, Germany
| | - Christine Beemelmanns
- Helmholtz Institute for Pharmaceutical Research Saarland, Helmholtz Centre for Infection Research, Saarbrücken, Germany
- Saarland University, Saarbrücken, Germany
| | - Hannes Link
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
| | - Christoph Mayer
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany
| | - Justin J J van der Hooft
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Bioinformatics Group, Wageningen University and Research, Wageningen, the Netherlands
- Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa
| | - Tito Damiani
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
| | - Tomáš Pluskal
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
| | - Pieter Dorrestein
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
| | - Jan Stanstrup
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg C, Denmark
| | - Robin Schmid
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic
| | - Mingxun Wang
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Department of Computer Science, University of California Riverside, Riverside, CA, USA
| | - Allegra Aron
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA
- Department of Chemistry and Biochemistry, University of Denver, Denver, CO, USA
| | - Madeleine Ernst
- Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen S, Denmark.
| | - Daniel Petras
- Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA.
- University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany.
- Department of Biochemistry, University of California Riverside, Riverside, CA, USA.
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3
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Tesfamariam K, Plekhova V, Gebreyesus SH, Lachat C, Alladio E, Argaw A, Endris BS, Roro M, De Saeger S, Vanhaecke L, De Boevre M. Rapid LA-REIMS-based metabolic fingerprinting of serum discriminates aflatoxin-exposed from non-exposed pregnant women: a prospective cohort from the Butajira Nutrition, Mental Health, and Pregnancy (BUNMAP) Study in rural Ethiopia. Mycotoxin Res 2024:10.1007/s12550-024-00558-x. [PMID: 39259493 DOI: 10.1007/s12550-024-00558-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 08/30/2024] [Accepted: 09/03/2024] [Indexed: 09/13/2024]
Abstract
To date, the changes in maternal metabolic response associated with prenatal aflatoxin exposure remain largely unknown. This study investigated the effects of prenatal aflatoxin exposure on the maternal serum metabolome in rural Ethiopia. A total of 309 pregnant women were enrolled prospectively, and their serum aflatoxin concentrations were measured using targeted liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Serum metabolic fingerprints were obtained using laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS), followed by combination of univariate and multivariate statistical modelling to evaluate changes in circulating metabolic features between aflatoxin-exposed and unexposed mothers and to select discriminatory metabolic features. The analysis revealed that 81.8% of women were exposed to aflatoxins, with a median concentration of 12.9 pg/mg albumin. The orthogonal partial least square discriminant analysis (OPLS-DA) regression model demonstrated significant disparities in the serum metabolome when comparing Ethiopian pregnant women with low vs high aflatoxin exposure. Thirty-two differentially expressed metabolic features were identified, affecting aminoacyl-tRNA biosynthesis pathway. Several discriminatory metabolites have been identified, including glutamine, tryptophan, tyrosine, carnosine, and 1-methylnicotinamide. In conclusion, our findings indicate that aflatoxin exposure during pregnancy have shown disparities in the maternal serum metabolome, primarily affecting protein synthesis. Further research is needed to identify specific metabolite biomarkers and elucidate the underlying mechanisms.
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Affiliation(s)
- Kokeb Tesfamariam
- Department of Food Technology, Safety, and Health, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
| | - Vera Plekhova
- Department of Translational Physiology, Infectiology and Public Health, Laboratory of Integrative Metabolomics, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Seifu H Gebreyesus
- Department of Nutrition and Dietetics, School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia
| | - Carl Lachat
- Department of Food Technology, Safety, and Health, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
| | | | - Alemayehu Argaw
- Department of Food Technology, Safety, and Health, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
| | - Bilal Shikur Endris
- Department of Nutrition and Dietetics, School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia
| | - Meselech Roro
- Department of Reproductive Health and Health Service Management, School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia
| | - Sarah De Saeger
- Center of Excellence in Mycotoxicology and Public Health, Faculty of Pharmaceutical Sciences, Ghent University, MYTOX-SOUTH® Coordination Unit, Ghent, Belgium
- Department of Biotechnology and Food Technology, Faculty of Science, University of Johannesburg, Doornfontein Campus, Gauteng, South Africa
| | - Lynn Vanhaecke
- Department of Translational Physiology, Infectiology and Public Health, Laboratory of Integrative Metabolomics, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
- School of Biological Sciences, Queen's University Belfast, Lisburn Road 97, Belfast, UK
| | - Marthe De Boevre
- Center of Excellence in Mycotoxicology and Public Health, Faculty of Pharmaceutical Sciences, Ghent University, MYTOX-SOUTH® Coordination Unit, Ghent, Belgium.
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4
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Yang X, Huang L, Zhang Y, Wang K, Liu S, Li X, Ding Y, Deng D, Zhang T, Zhao W, Ma L, Wang Y, Shu S, Chen X. Untargeted metabolomics and mendelian randomization analysis identify alpha-linolenic acid and linoleic acid as novel biomarkers of perioperative neurocognitive dysfunction. Clin Nutr 2024; 43:2198-2210. [PMID: 39163761 DOI: 10.1016/j.clnu.2024.07.039] [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: 03/14/2024] [Revised: 07/27/2024] [Accepted: 07/29/2024] [Indexed: 08/22/2024]
Abstract
Perioperative neurocognitive dysfunction (PND) occurs in elderly individuals undergoing anesthesia and surgery. To explore the potential molecular mechanisms, we performed right-sided cervical exploratory surgery under sevoflurane anesthesia in 18-month-old male Sprague-Dawley rats. Anxiety-depression-like behaviors and learning memory abilities were assessed using the Open Field Test (OFT) and Novel Object Recognition (NOR). Additionally, the hippocampus was collected one day after surgery for inflammatory factor detection, TUNEL staining, and metabolomics analysis. Mendelian randomization (MR) analyses were subsequently conducted to validate the causal relationships by using a series of GWAS datasets related to representative differential metabolites as exposures and cognitive impairment as endpoints. The results indicated that rats exposed to anesthesia and surgery exhibited poorer cognitive performance, significant elevations in hippocampal inflammatory factors such as IL-1β and TNF-α, and extensive neuronal apoptosis. LC-MS/MS-based untargeted metabolomics identified 19 up-regulated and 32 down-regulated metabolites in the test group, with 6 differential metabolites involved in metabolic pathways enriched according to the KEGG database. ROC analysis revealed a correlation between α-linolenic acid (ALA) and linoleic acid (LA) and the development of PND. Further MR analysis confirmed that ALA was significantly associated with cognitive performance and the risk of depression, while LA was significantly associated with the risk of memory loss. Taken together, our results identified ALA and LA as potentially powerful biomarkers for PND.
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Affiliation(s)
- Xinxin Yang
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Li Huang
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Yanyan Zhang
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Kaixin Wang
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Shiya Liu
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Xiaojin Li
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Yuanyuan Ding
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Daling Deng
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Tianhao Zhang
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Wenjing Zhao
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Lulin Ma
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Yafeng Wang
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Shaofang Shu
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China
| | - Xiangdong Chen
- Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China.
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5
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Li J, Jiang J, Zhu Y, Zhang Y, Zhu J, Ming Y. Metabolomics analysis of patients with Schistosoma japonicum infection based on UPLC-MS method. Parasit Vectors 2024; 17:350. [PMID: 39164750 PMCID: PMC11334362 DOI: 10.1186/s13071-024-06429-9] [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: 03/20/2024] [Accepted: 07/30/2024] [Indexed: 08/22/2024] Open
Abstract
BACKGROUND Schistosomiasis is still one of the most serious parasitic diseases. Evidence showed that the metabolite profile in serum can potentially act as a marker for parasitic disease diagnosis and evaluate disease progression and prognosis. However, the serum metabolome in patients with Schistosoma japonicum infection is not well defined. In this study, we investigated the metabolite profiles of patients with chronic and with advanced S. japonicum infection. METHODS The sera of 33 chronic S. japonicum patients, 15 patients with advanced schistosomiasis and 17 healthy volunteers were collected. Samples were extracted for metabolites and analyzed with ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). RESULTS We observed significant differences in metabolite profiles in positive and negative ion modes between patients with advanced and chronic S. japonicum infection. In patients with chronic S. japonicum infection, 199 metabolites were significantly upregulated while 207 metabolites were downregulated in advanced infection. These differential metabolites were mainly concentrated in steroid hormone biosynthesis, cholesterol metabolism and bile secretion pathways. We also found that certain bile acid levels were significantly upregulated in the progression from chronic to advanced S. japonicum infection. In receiver operator characteristic (ROC) analysis, we identified three metabolites with area under the curve (AUC) > 0.8, including glycocholic (GCA), glycochenodeoxycholate (GCDCA) and taurochenodeoxycholic acid (TCDCA) concentrated in cholesterol metabolism, biliary secretion and primary bile acid biosynthesis. CONCLUSIONS This study provides evidence that GCA, GCDCA and TCDCA can potentially act as novel metabolite biomarkers to distinguish patients in different stages of S. japonicum infection. This study will contribute to the understanding of the metabolite mechanisms of the transition from chronic to advanced S. japonicum infection, although more studies are needed to validate this potential role and explore the underlying mechanisms.
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Affiliation(s)
- Junhui Li
- Center for Organ Transplantation, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
- Key Laboratory of Translational Research in Transplantion Medicine of National Health Commission, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
- Hunan Province Clinical Research Center for Infectious Diseases, Changsha, 410013, Hunan, China
| | - Jie Jiang
- Center for Organ Transplantation, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
- Key Laboratory of Translational Research in Transplantion Medicine of National Health Commission, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
- Hunan Province Clinical Research Center for Infectious Diseases, Changsha, 410013, Hunan, China
| | - Yi Zhu
- Center for Organ Transplantation, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
- Key Laboratory of Translational Research in Transplantion Medicine of National Health Commission, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
- Hunan Province Clinical Research Center for Infectious Diseases, Changsha, 410013, Hunan, China
| | - Yu Zhang
- Center for Organ Transplantation, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
- Key Laboratory of Translational Research in Transplantion Medicine of National Health Commission, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
- Hunan Province Clinical Research Center for Infectious Diseases, Changsha, 410013, Hunan, China
| | - Jiang Zhu
- Center for Organ Transplantation, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
- Key Laboratory of Translational Research in Transplantion Medicine of National Health Commission, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
- Hunan Province Clinical Research Center for Infectious Diseases, Changsha, 410013, Hunan, China
| | - Yingzi Ming
- Center for Organ Transplantation, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
- Key Laboratory of Translational Research in Transplantion Medicine of National Health Commission, Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
- Hunan Province Clinical Research Center for Infectious Diseases, Changsha, 410013, Hunan, China.
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Beger RD, Goodacre R, Jones CM, Lippa KA, Mayboroda OA, O'Neill D, Najdekr L, Ntai I, Wilson ID, Dunn WB. Analysis types and quantification methods applied in UHPLC-MS metabolomics research: a tutorial. Metabolomics 2024; 20:95. [PMID: 39110307 PMCID: PMC11306277 DOI: 10.1007/s11306-024-02155-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 07/16/2024] [Indexed: 08/10/2024]
Abstract
BACKGROUND Different types of analytical methods, with different characteristics, are applied in metabolomics and lipidomics research and include untargeted, targeted and semi-targeted methods. Ultra High Performance Liquid Chromatography-Mass Spectrometry is one of the most frequently applied measurement instruments in metabolomics because of its ability to detect a large number of water-soluble and lipid metabolites over a wide range of concentrations in short analysis times. Methods applied for the detection and quantification of metabolites differ and can either report a (normalised) peak area or an absolute concentration. AIM OF REVIEW In this tutorial we aim to (1) define similarities and differences between different analytical approaches applied in metabolomics and (2) define how amounts or absolute concentrations of endogenous metabolites can be determined together with the advantages and limitations of each approach in relation to the accuracy and precision when concentrations are reported. KEY SCIENTIFIC CONCEPTS OF REVIEW The pre-analysis knowledge of metabolites to be targeted, the requirement for (normalised) peak responses or absolute concentrations to be reported and the number of metabolites to be reported define whether an untargeted, targeted or semi-targeted method is applied. Fully untargeted methods can only provide (normalised) peak responses and fold changes which can be reported even when the structural identity of the metabolite is not known. Targeted methods, where the analytes are known prior to the analysis, can also report fold changes. Semi-targeted methods apply a mix of characteristics of both untargeted and targeted assays. For the reporting of absolute concentrations of metabolites, the analytes are not only predefined but optimized analytical methods should be developed and validated for each analyte so that the accuracy and precision of concentration data collected for biological samples can be reported as fit for purpose and be reviewed by the scientific community.
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Affiliation(s)
- Richard D Beger
- National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Royston Goodacre
- Department of Biochemistry, Cell and Systems Biology, Centre for Metabolomics Research, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Christina M Jones
- Office of Advanced Manufacturing, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Katrice A Lippa
- Office of Weights and Measures, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Oleg A Mayboroda
- Center for Proteomics and Metabolomics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Donna O'Neill
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, UK
| | - Lukas Najdekr
- Faculty of Medicine and Dentistry, Institute of Molecular and Translational Medicine, Palacký University Olomouc, 779 00, Olomouc, Czech Republic
| | - Ioanna Ntai
- BioMarin Pharmaceutical Inc., San Rafael, CA, USA
| | - Ian D Wilson
- Department of Biochemistry, Cell and Systems Biology, Centre for Metabolomics Research, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
- Computational and Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Warwick B Dunn
- Department of Biochemistry, Cell and Systems Biology, Centre for Metabolomics Research, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK.
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Comesaña S, Antomagesh F, Soengas JL, Blanco AM, Vijayan MM. Valine administration in the hypothalamus alters the brain and plasma metabolome in rainbow trout. Am J Physiol Regul Integr Comp Physiol 2024; 327:R261-R273. [PMID: 38881412 DOI: 10.1152/ajpregu.00056.2024] [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: 03/03/2024] [Revised: 05/28/2024] [Accepted: 06/06/2024] [Indexed: 06/18/2024]
Abstract
Central administration of valine has been shown to cause hyperphagia in fish. Although mechanistic target of rapamycin (mTOR) is involved in this response, the contributions to feed intake of central and peripheral metabolite changes due to excess valine are unknown. Here, we investigated whether intracerebroventricular injection of valine modulates central and peripheral metabolite profiles and may provide insights into feeding response in fish. Juvenile rainbow trout (Oncorhynchus mykiss) were administered an intracerebroventricular injection of valine (10 µg·µL-1 at 1 μL·100·g-1 body wt), and the metabolite profile in plasma, hypothalamus, and rest of the brain (composing of telencephalon, optic tectum, cerebellum, and medulla oblongata) was carried out by liquid chromatography-mass spectrometry (LC/MS)-based metabolomics. Valine administration led to a spatially distinct metabolite profile at 1 h postinjection in the brain: enrichment of amino acid metabolism and energy production pathways in the rest of the brain but not in hypothalamus. This suggests a role for extrahypothalamic input in the regulation of feed intake. Also, there was enrichment of several amino acids, including tyrosine, proline, valine, phenylalanine, and methionine, in plasma in response to valine. Changes in liver transcript abundance and protein expression reflect an increased metabolic capacity, including energy production from glucose and fatty acids, and a lower protein kinase B (Akt) phosphorylation in the valine group. Altogether, valine intracerebroventricular administration affects central and peripheral metabolism in rainbow trout, and we propose a role for the altered metabolite profile in modulating the feeding response to this branched-chain amino acid.NEW & NOTEWORTHY Valine causes hyperphagia in fish when it is centrally administered; however, the exact mechanisms are far from clear. We tested how intracerebroventricular injection of valine in rainbow trout affected the brain and plasma metabolome. The metabolite changes in response to valine were more evident in the rest of the brain compared with the hypothalamus. Furthermore, we demonstrated for the first time that central valine administration affects peripheral metabolism in rainbow trout.
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Affiliation(s)
- Sara Comesaña
- Centro de Investigación Mariña, Laboratorio de Fisioloxía Animal, Departamento de Bioloxía Funcional e Ciencias da Saúde, Facultade de Bioloxía, Universidade de Vigo, Vigo, Spain
| | | | - José L Soengas
- Centro de Investigación Mariña, Laboratorio de Fisioloxía Animal, Departamento de Bioloxía Funcional e Ciencias da Saúde, Facultade de Bioloxía, Universidade de Vigo, Vigo, Spain
| | - Ayelén M Blanco
- Centro de Investigación Mariña, Laboratorio de Fisioloxía Animal, Departamento de Bioloxía Funcional e Ciencias da Saúde, Facultade de Bioloxía, Universidade de Vigo, Vigo, Spain
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8
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Wang W, Liu L, Qiu W, Chen C, Huang Y, Cai A, Nie Z, Ou Y, Zhu Y, Feng Y. The Non-Targeted Lipidomic-Based Classifier Reveals Two Candidate Biomarkers for Ischemic Stroke in Hypertensive Individuals. Risk Manag Healthc Policy 2024; 17:1889-1901. [PMID: 39100548 PMCID: PMC11297523 DOI: 10.2147/rmhp.s465135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 07/11/2024] [Indexed: 08/06/2024] Open
Abstract
Introduction Traditional clinical risk factors are insufficient to estimate the residual risk of large-vessel ischemic stroke. Non-targeted lipidomic techniques provide an opportunity to evaluate these risks. Methods Plasma samples were collected from 113 hypertensive individuals, including 55 individuals at high risk of ischemic stroke and 58 matched individuals, in a prospective nested case-control cohort. To identify dysregulated lipid metabolites, we conducted multivariate and univariate analyses. A classifier based on a cross-validated procedure was employed to select the optimal combination of lipid species and their ratios. Results We identified 23 dysregulated lipid species in patients with and without ischemic stroke, including 16 (69.6%) up-regulated and 7 (30.4%) down-regulated lipid species. Through internal cross-validation, the optimal combination of two lipid features (phosphatidylcholine 34:2 and triglyceride 18:1/18:1/22:1 / phosphatidylcholine 34:2, referred to as ischemic stroke-related 2 lipid features - IS2LP) was selected, leading to a more precise prediction probability for ischemic stroke within 3.9 years. In the comparison of different risk factors, the traditional risk score, the IS2LP risk score, and the combination of the traditional risk score with IS2LP yield AUC values of 0.613(95% CI:0.509-0.717), 0.833(95% CI:0.755-0.911), and 0.843(95% CI:0.777-0.916), respectively. The combination of the traditional risk score and IS2LP exhibited significantly improved discriminative performance, with an integrated discrimination improvement (IDI) of 0.31 (p<0.001) and a continuous net reclassification improvement (NRI) of 1.06 (p < 0.001) compared to the traditional risk score. Conclusion We identified new lipidomic biomarkers associated with the futural event of large-vessel ischemic stroke. These lipid species could serve as potential blood biomarkers for assessing the residual risk of ischemic stroke in hypertensive individuals.
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Affiliation(s)
- Wenbin Wang
- Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
| | - Lin Liu
- Department of Medicine, The University of Hong Kong, Hong Kong, China
| | - Weida Qiu
- Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
| | - Chaolei Chen
- Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
| | - Yuqing Huang
- Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
| | - Anping Cai
- Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
| | - Zhiqiang Nie
- Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
| | - Yanqiu Ou
- Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
| | - Yicheng Zhu
- Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
| | - Yingqing Feng
- Department of Cardiology, Hypertension Research Laboratory, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
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9
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Zhou M, Liu X, Wu Y, Xiang Q, Yu R. Liver Lipidomics Analysis Revealed the Protective mechanism of Zuogui Jiangtang Qinggan Formula in type 2 diabetes mellitus with non-alcoholic fatty liver disease. JOURNAL OF ETHNOPHARMACOLOGY 2024; 329:118160. [PMID: 38588985 DOI: 10.1016/j.jep.2024.118160] [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: 12/01/2023] [Revised: 03/23/2024] [Accepted: 04/05/2024] [Indexed: 04/10/2024]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Hepatic steatosis, a hallmark of non-alcoholic fatty liver disease (NAFLD), represents a significant global health issue. Liver lipidomics has garnered increased focus recently, highlighting Traditional Chinese Medicine's (TCM) role in mitigating such conditions through lipid metabolism regulation. The Zuogui Jiangtang Qinggan Formula (ZGJTQGF), a longstanding TCM regimen for treating Type 2 Diabetes Mellitus (T2DM) with NAFLD, lacks a definitive mechanism for its lipid metabolism regulatory effects. AIM OF THE STUDY This research aims to elucidate ZGJTQGF's mechanism on lipid metabolism in T2DM with NAFLD. MATERIALS AND METHODS The study, utilized db/db mice to establish T2DM with NAFLD models. Evaluations included Hematoxylin-Eosin (HE) and Oil Red O stainedstaining of liver tissues, alongside biochemical lipid parameter analysis. Liver lipidomics and Western blotting further substantiated the findings, systematically uncovering the mechanism of action mechanism. RESULTS ZGJTQGF notably reduced body weight, and Fasting Blood Glucose (FBG), enhancing glucose tolerance in db/db mice. HE, and Oil Red O staining, complemented by biochemical and liver lipidomics analyses, confirmed ZGJTQGF's efficacy in ameliorating liver steatosis and lipid metabolism anomalies. Lipidomics identified 1571 significantly altered lipid species in the model group, primarily through the upregulation of triglycerides (TG) and diglycerides (DG), and the downregulation of phosphatidylcholine (PC) and phosphatidylethanolamine (PE). Post-ZGJTQGF treatment, 496 lipid species were modulated, with increased PC and PE levels and decreased TG and DG, showcasing significant lipid metabolism improvement in T2DM with NAFLD. Moreover, ZGJTQGF's influence on lipid synthesis-related proteins was observed, underscoring its anti-steatotic impact through liver lipidomic alterations and offering novel insights into hepatic steatosis pathogenesis. CONCLUSIONS Liver lipidomics analysis combined with protein verification further demonstrated that ZGJTQGF could ameliorate the lipid disturbance of TG, DG, PC, PE in T2DM with NAFLD, as well as improve fatty acid and cholesterol synthesis and metabolism through De novo lipogenesis pathway.
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Affiliation(s)
- Min Zhou
- Hunan University of Traditional Chinese Medicine, 300 Xueshi Road, Changsha, Hunan 410208, China; Hunan Provincial Key Laboratory of Translational Research in TCM Prescriptions and Zheng, Hunan University of Traditional Chinese Medicine, 300 Xueshi Road, Changsha, Hunan, 410208, China
| | - Xiu Liu
- Hunan University of Traditional Chinese Medicine, 300 Xueshi Road, Changsha, Hunan 410208, China
| | - Yongjun Wu
- Hunan University of Traditional Chinese Medicine, 300 Xueshi Road, Changsha, Hunan 410208, China
| | - Qin Xiang
- Hunan University of Traditional Chinese Medicine, 300 Xueshi Road, Changsha, Hunan 410208, China; Hunan Provincial Key Laboratory of Translational Research in TCM Prescriptions and Zheng, Hunan University of Traditional Chinese Medicine, 300 Xueshi Road, Changsha, Hunan, 410208, China.
| | - Rong Yu
- Hunan University of Traditional Chinese Medicine, 300 Xueshi Road, Changsha, Hunan 410208, China; Hunan Provincial Key Laboratory of Translational Research in TCM Prescriptions and Zheng, Hunan University of Traditional Chinese Medicine, 300 Xueshi Road, Changsha, Hunan, 410208, China.
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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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11
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Yang J, Zhou Y, Wang T, Li N, Chao Y, Gao S, Zhang Q, Wu S, Zhao L, Dong X. A multi-omics study to monitor senescence-associated secretory phenotypes of Alzheimer's disease. Ann Clin Transl Neurol 2024; 11:1310-1324. [PMID: 38605603 DOI: 10.1002/acn3.52047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 03/04/2024] [Accepted: 03/10/2024] [Indexed: 04/13/2024] Open
Abstract
OBJECTIVE Alzheimer's disease (AD) is characterized by the progressive degeneration and damage of neurons in the brain. However, developing an accurate diagnostic assay using blood samples remains a challenge in clinic practice. The aim of this study was to explore senescence-associated secretory phenotypes (SASPs) in peripheral blood using mass spectrometry based multi-omics approach and to establish diagnostic assays for AD. METHODS This retrospective study included 88 participants, consisting of 29 AD patients and 59 cognitively normal (CN) individuals. Plasma and serum samples were examined using high-resolution mass spectrometry to identify proteomic and metabolomic profiles. Receiver operating characteristic (ROC) analysis was employed to screen biomarkers with diagnostic potential. K-nearest neighbors (KNN) algorithm was utilized to construct a multi-dimensional model for distinguishing AD from CN. RESULTS Proteomics analysis revealed upregulation of five plasma proteins in AD, including RNA helicase aquarius (AQR), zinc finger protein 587B (ZNF587B), C-reactive protein (CRP), fibronectin (FN1), and serum amyloid A-1 protein (SAA1), indicating their potential for AD classification. Interestingly, KNN-based three-dimensional model, comprising AQR, ZNF587B, and CRP, demonstrated its high accuracy in AD recognition, with evaluation possibilities of 0.941, 1.000, and 1.000 for the training, testing, and validation datasets, respectively. Besides, metabolomics analysis suggested elevated levels of serum phenylacetylglutamine (PAGIn) in AD. INTERPRETATION The multi-omics outcomes highlighted the significance of the SASPs, specifically AQR, ZNF587B, CRP, and PAGIn, in terms of their potential for diagnosing AD and suggested neuronal aging-associated pathophysiology.
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Affiliation(s)
- Jingzhi Yang
- Institute of Translational Medicine, Shanghai University, Shanghai, 200444, China
| | - Yinge Zhou
- School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Tianjiao Wang
- School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Na Li
- School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Yufan Chao
- School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Songyan Gao
- Institute of Translational Medicine, Shanghai University, Shanghai, 200444, China
| | - Qun Zhang
- Department of Internal Medicine, Shanghai Baoshan Elderly Nursing Hospital, Shanghai, 200435, China
| | - Shuo Wu
- Neurology Department, Shanghai Baoshan Luodian Hospital, Shanghai, 201908, China
| | - Liang Zhao
- Department of Pharmacy, Shanghai Baoshan Luodian Hospital, Shanghai, 201908, China
| | - Xin Dong
- Institute of Translational Medicine, Shanghai University, Shanghai, 200444, China
- School of Medicine, Shanghai University, Shanghai, 200444, China
- Suzhou Innovation Center of Shanghai University, Suzhou, 215000, Jiangsu, China
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Tardif C, Rouger C, Miranda J, Ahmed OS, Richard-Forget F, Atanasova V, Waffo-Teguo P. Targeting of Antifungal Metabolites from Grapevine Byproducts by UPLC-HRMS/MS Approaches Using Bioactivity-Based Molecular Networking. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:9621-9636. [PMID: 38648422 DOI: 10.1021/acs.jafc.3c09531] [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: 04/25/2024]
Abstract
This study focuses on countering Fusarium graminearum, a harmful fungal pathogen impacting cereal crops and human health through mycotoxin production. These mycotoxins, categorized as type B trichothecenes, pose significant health risks. Research explores natural alternatives to synthetic fungicides, particularly investigating phenolics in grapevine byproducts. Thirteen eco-extracts from five French grape varieties (Merlot, Cabernet Sauvignon, Sauvignon blanc, Tannat, and Artaban) exhibited substantial antifungal properties, with ten extracts displaying remarkable effects. Extracts from grapevine stems and roots notably reduced fungal growth by over 91% after five days. Through UHPLC-HRMS/MS analysis and metabolomics, the study identified potent antifungal compounds such as ampelopsin A and cyphostemmin B, among other oligomeric stilbenes. Interestingly, this approach showed that flavan-3-ols have been identified as markers for extracts that induce fungal growth. Root extracts from rootstocks, rich in oligostilbenes, demonstrated the highest antifungal activity. This research underscores grapevine byproducts' potential both as a sustainable approach to control F. graminearum and mycotoxin contamination in cereal crops and the presence of different metabolites from the cultivars of grapevine, suggesting different activities.
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Affiliation(s)
- Charles Tardif
- University of Bordeaux, UMR INRAE 1366, Bordeaux INP, OENO, ISVV, F-33140 Villenave d'Ornon, France
- Bordeaux Sciences Agro, UMR INRAE 1366, Bordeaux INP, OENO, ISVV, F-33170 Gradignan, France
| | - Caroline Rouger
- University of Bordeaux, UMR INRAE 1366, Bordeaux INP, OENO, ISVV, F-33140 Villenave d'Ornon, France
- Bordeaux Sciences Agro, UMR INRAE 1366, Bordeaux INP, OENO, ISVV, F-33170 Gradignan, France
- Bordeaux Metabolome, MetaboHUB, PHENOME-EMPHASIS, Centre INRAE de Nouvelle Aquitaine-Bordeaux, F-33140 Villenave d'Ornon, France
| | - Julie Miranda
- University of Bordeaux, UMR INRAE 1366, Bordeaux INP, OENO, ISVV, F-33140 Villenave d'Ornon, France
- Bordeaux Sciences Agro, UMR INRAE 1366, Bordeaux INP, OENO, ISVV, F-33170 Gradignan, France
| | - Omar S Ahmed
- University of Bordeaux, UMR INRAE 1366, Bordeaux INP, OENO, ISVV, F-33140 Villenave d'Ornon, France
- Bordeaux Sciences Agro, UMR INRAE 1366, Bordeaux INP, OENO, ISVV, F-33170 Gradignan, France
- Department of Analytical Chemistry, Faculty of Pharmacy, Misr University for Science and Technology (MUST), Al-Motamayez District, P.O. Box 77, 3236101 6th of October City, Egypt
| | | | - Vessela Atanasova
- INRAE, UR 1264 Mycology and Food Safety (MycSA), F-33882 Villenave d'Ornon, France
| | - Pierre Waffo-Teguo
- University of Bordeaux, UMR INRAE 1366, Bordeaux INP, OENO, ISVV, F-33140 Villenave d'Ornon, France
- Bordeaux Sciences Agro, UMR INRAE 1366, Bordeaux INP, OENO, ISVV, F-33170 Gradignan, France
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Robeyns R, Sisto A, Iturrospe E, da Silva KM, van de Lavoir M, Timmerman V, Covaci A, Stroobants S, van Nuijs ALN. The Metabolic and Lipidomic Fingerprint of Torin1 Exposure in Mouse Embryonic Fibroblasts Using Untargeted Metabolomics. Metabolites 2024; 14:248. [PMID: 38786725 PMCID: PMC11123261 DOI: 10.3390/metabo14050248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 04/22/2024] [Accepted: 04/23/2024] [Indexed: 05/25/2024] Open
Abstract
Torin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a reliable and thorough untargeted metabolomics workflow to study torin1-induced metabolic changes in mouse embryonic fibroblast (MEF) cells. Crucially, our quality assurance and quality control (QA/QC) protocols were designed to increase confidence in the reported findings by reducing the likelihood of false positives, including a validation experiment replicating all experimental steps from sample preparation to data analysis. This study investigated the metabolic fingerprint of torin1 exposure by using liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics platforms. Our workflow identified 67 altered metabolites after torin1 exposure, combining univariate and multivariate statistics and the implementation of a validation experiment. In particular, intracellular ceramides, diglycerides, phosphatidylcholines, phosphatidylethanolamines, glutathione, and 5'-methylthioadenosine were downregulated. Lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, glycerophosphocholine, triglycerides, inosine, and hypoxanthine were upregulated. Further biochemical pathway analyses provided deeper insights into the reported changes. Ultimately, our study provides a valuable workflow that can be implemented for future investigations into the effects of other compounds, including more specific autophagy modulators.
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Affiliation(s)
- Rani Robeyns
- Toxicological Centre, University of Antwerp, 2610 Antwerp, Belgium; (E.I.); (A.C.)
| | - Angela Sisto
- Peripheral Neuropathy Research Group, University of Antwerp, 2610 Antwerp, Belgium
| | - Elias Iturrospe
- Toxicological Centre, University of Antwerp, 2610 Antwerp, Belgium; (E.I.); (A.C.)
- Department of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel, 1090 Brussels, Belgium
| | | | - Maria van de Lavoir
- Toxicological Centre, University of Antwerp, 2610 Antwerp, Belgium; (E.I.); (A.C.)
| | - Vincent Timmerman
- Peripheral Neuropathy Research Group, University of Antwerp, 2610 Antwerp, Belgium
| | - Adrian Covaci
- Toxicological Centre, University of Antwerp, 2610 Antwerp, Belgium; (E.I.); (A.C.)
| | - Sigrid Stroobants
- Department of Nuclear Medicine, Antwerp University Hospital, 2650 Antwerp, Belgium
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Guo X, Ou T, Yang X, Song Q, Zhu L, Mi S, Zhang J, Zhang Y, Chen W, Guo J. Untargeted metabolomics based on ultra-high performance liquid chromatography-mass spectrometry/MS reveals the lipid-lowering mechanism of taurine in hyperlipidemia mice. Front Nutr 2024; 11:1367589. [PMID: 38706565 PMCID: PMC11066166 DOI: 10.3389/fnut.2024.1367589] [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: 01/09/2024] [Accepted: 04/03/2024] [Indexed: 05/07/2024] Open
Abstract
Introduction Taurine has a prominent lipid-lowering effect on hyperlipidemia. However, a comprehensive analysis of the effects of taurine on endogenous metabolites in hyperlipidemia has not been documented. This study aimed to explore the impact of taurine on multiple metabolites associated with hyperlipidemia. Methods The hyperlipidemic mouse model was induced by high-fat diet (HFD). Taurine was administered via oral gavage at doses of 700 mg/kg/day for 14 weeks. Evaluation of body weight, serum lipid levels, and histopathology of the liver and adipose tissue was performed to confirm the lipid-lowering effect of taurine. Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS)-based metabonomics analyses of serum, urine, feces, and liver, coupled with multivariate data analysis, were conducted to assess changes in the endogenous metabolites. Results and discussion Biochemical and histological examinations demonstrated that taurine administration prevented weight gain and dyslipidemia, and alleviated lipid deposition in the liver and adipose tissue in hyperlipidemic mice. A total of 76 differential metabolites were identified by UPLC-MS-based metabolomics approach, mainly involving BAs, GPs, SMs, DGs, TGs, PUFAs and amino acids. Taurine was found to partially prevent HFDinduced abnormalities in the aforementioned metabolites. Using KEGG database and MetaboAnalyst software, it was determined that taurine effectively alleviates metabolic abnormalities caused by HFD, including fatty acid metabolism, sphingolipid metabolism, glycerophospholipid metabolism, diacylglycerol metabolism, amino acid metabolism, bile acid and taurine metabolism, taurine and hypotaurine metabolism. Moreover, DGs, GPs and SMs, and taurine itself may serve as active metabolites in facilitating various anti-hyperlipidemia signal pathways associated with taurine. This study provides new evidence for taurine to prevent hyperlipidemia.
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Affiliation(s)
- Xinzhe Guo
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Tong Ou
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Xinyu Yang
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Qi Song
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Lin Zhu
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Shengquan Mi
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Jing Zhang
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Yanzhen Zhang
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Wen Chen
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
| | - Junxia Guo
- Beijing Key Laboratory of Bioactive Substances and Functional Foods, Beijing Union University, Beijing, China
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Li J, Wang F, Sayed MA, Shen X, Zhou L, Liu X, Sun X, Chen S, Wu Y, Lu L, Gong S, Iqbal A, Yang Y. Integrated transcriptomic and metabolomic data reveal the cold stress responses molecular mechanisms of two coconut varieties. FRONTIERS IN PLANT SCIENCE 2024; 15:1353352. [PMID: 38689842 PMCID: PMC11058665 DOI: 10.3389/fpls.2024.1353352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 03/29/2024] [Indexed: 05/02/2024]
Abstract
Among tropical fruit trees, coconut holds significant edible and economic importance. The natural growth of coconuts faces a challenge in the form of low temperatures, which is a crucial factor among adverse environmental stresses impacting their geographical distribution. Hence, it is essential to enhance our comprehension of the molecular mechanisms through which cold stress influences various coconut varieties. We employed analyses of leaf growth morphology and physiological traits to examine how coconuts respond to low temperatures over 2-hour, 8-hour, 2-day, and 7-day intervals. Additionally, we performed transcriptome and metabolome analyses to identify the molecular and physiological shifts in two coconut varieties displaying distinct sensitivities to the cold stress. As the length of cold stress extended, there was a prominent escalation within the soluble protein (SP), proline (Pro) concentrations, the activity of peroxidase (POD) and superoxide dismutase (SOD) in the leaves. Contrariwise, the activity of glutathione peroxidase (GSH) underwent a substantial reduction during this period. The widespread analysis of metabolome and transcriptome disclosed a nexus of genes and metabolites intricately cold stress were chiefly involved in pathways centered around amino acid, flavonoid, carbohydrate and lipid metabolism. We perceived several stress-responsive metabolites, such as flavonoids, carbohydrates, lipids, and amino acids, which unveiled considerably, lower in the genotype subtle to cold stress. Furthermore, we uncovered pivotal genes in the amino acid biosynthesis, antioxidant system and flavonoid biosynthesis pathway that presented down-regulation in coconut varieties sensitive to cold stress. This study broadly enriches our contemporary perception of the molecular machinery that contributes to altering levels of cold stress tolerance amid coconut genotypes. It also unlocks several unique prospects for exploration in the areas of breeding or engineering, aiming to identifying tolerant and/or sensitive coconut varieties encompassing multi-omics layers in response to cold stress conditions.
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Affiliation(s)
- Jing Li
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
| | - Fangyuan Wang
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
| | - Md. Abu Sayed
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
| | - XiaoJun Shen
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
| | - Lixia Zhou
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
| | - Xiaomei Liu
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
| | - Xiwei Sun
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
| | - Shuangyan Chen
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
- School of Tropical Crops, Yunnan Agricultural University, Kunming, Yunnan, China
| | - Yi Wu
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
| | - Lilan Lu
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
| | - Shufang Gong
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
| | - Amjad Iqbal
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
- Department of Food Science & Technology, Abdul Wali Khan University Mardan, Mardan, Pakistan
| | - Yaodong Yang
- Coconut Research Institute, Chinese Academy of Tropical Agricultural Sciences/Hainan Key Laboratory of Tropical Oil Crops Biology, Wenchang, Hainan, China
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16
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Tang B, Hao Y, Wang C, Deng Z, Kou Z, Zhou H, Zhang H, Fan F, Wang K, Wang D. Biological characteristics of pregnancy in captive Yangtze finless porpoises revealed by urinary metabolomics†. Biol Reprod 2024; 110:808-818. [PMID: 38169437 PMCID: PMC11017131 DOI: 10.1093/biolre/ioad175] [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: 07/07/2023] [Revised: 11/20/2023] [Accepted: 12/19/2023] [Indexed: 01/05/2024] Open
Abstract
The Yangtze finless porpoises (Neophocaena asiaeorientalis a.) are an endemic and critically endangered species in China. Intensive captive breeding is essential for understanding the biology of critically endangered species, especially their pregnancy characteristics, knowledge of which is crucial for effective breeding management. Urine metabolomics can reveal metabolic differences, arising from physiological changes across pregnancy stages. Therefore, we used the urinary metabolomic technology, to explore urinary metabolite changes in pregnant Yangtze finless porpoises. A total of 2281 metabolites were identified in all samples, which including organic acids and derivatives (24.45%), organoheterocyclic compounds (20.23%), benzenoids (18.05%), organic oxygen compounds (7.73%), and phenylpropanoids and polyketides (6.48%). There were 164, 387, and 522 metabolites demonstrating differential abundance during early pregnancy, mid pregnancy, and late pregnancy, respectively, from the levels observed in nonpregnancy. The levels of pregnenolone, 17α-hydroxyprogesterone, and tetrahydrocortisone were significantly higher during all pregnancy stages, indicating their important roles in fetal development. The differential metabolites between nonpregnancy and pregnancy were mainly associated with amino acid and carbohydrate metabolism. Moreover, metabolic activity varied across pregnancy stages; steroid hormone biosynthesis was predominant in early pregnancy, and amino acid biosynthesis and carbohydrate metabolism were predominant in mid pregnancy and late pregnancy, respectively. Our results provide new insights into metabolic characteristics in the Yangtze finless porpoises' urine during pregnancy, and indicate that the differential levels of urine metabolites can determine pregnancy in Yangtze finless porpoises, providing valuable information for the husbandry and management of pregnant Yangtze finless porpoises in captivity.
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Affiliation(s)
- Bin Tang
- Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
| | - Yujiang Hao
- Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- National Aquatic Biological Resource Center, NABRC, Wuhan, China
| | - Chaoqun Wang
- Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- National Aquatic Biological Resource Center, NABRC, Wuhan, China
| | - Zhengyu Deng
- Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- National Aquatic Biological Resource Center, NABRC, Wuhan, China
| | - Zhangbing Kou
- Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
| | - Haojie Zhou
- Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Haobo Zhang
- Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Fei Fan
- Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- National Aquatic Biological Resource Center, NABRC, Wuhan, China
| | - Kexiong Wang
- Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- National Aquatic Biological Resource Center, NABRC, Wuhan, China
| | - Ding Wang
- Key Laboratory of Aquatic Biodiversity and Conservation, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- National Aquatic Biological Resource Center, NABRC, Wuhan, China
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Wang N, Sieng S, Liang T, Xu J, Han Q. Intestine proteomic and metabolomic alterations in dogs infected with Toxocara canis. Acta Trop 2024; 252:107140. [PMID: 38341054 DOI: 10.1016/j.actatropica.2024.107140] [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: 11/02/2023] [Revised: 01/31/2024] [Accepted: 01/31/2024] [Indexed: 02/12/2024]
Abstract
Toxocariasis is an important zoonotic parasitic disease. Toxocaris canis adults live and reproduce in the intestinal tract of dogs and other canine hosts, and the infectious eggs are continuously excreted in feces, which causes environmental contamination and has an important public health significance. In this study, TMT proteomic and untargeted metabolomic methods were used to explore the physiological and pathological effects on the intestinal tract of dogs which infected with T. canis, and a series of bioinformatics analyses were conducted to identify differentially expressed proteins (DEPs) and differentially expressed metabolites (DEMs). The proteomics results showed that 198 DEPs were mainly enriched in the immune system and signal transduction pathway, and involved in the regulation of the occurrence and development of cancer and infectious diseases. T. canis could disrupt intestinal permeability by increasing the expression of proteins such as zinc finger protein DZIP1L and myosin heavy chain 10. Additionally, T. canis infection could also inhibit the host immune response by decreasing the expression of MHC-II, NF-κB, DLA and other immune-related molecules. While, the metabolomics results revealed that the expression of oxoglutaric acid, glutamate, d-aspartate, arginine, taurochenodeoxycholic acid and taurocholic acid which participated in tricarboxylic acid (TCA) cycle, glycolysis/gluconeogenesis, bile secretion, biosynthesis of amino acids pathway were significantly decreased. The correlation results of proteomics and metabolomics showed that DEPs and DEMs were mainly co-enriched in bile secretion pathway to regulate intestinal peristalsis. Analyzing DEPs and DEMs will not only provide insights into the mechanisms of host parasite interaction, but also aid in identifying potential targets for therapy and diagnosis, thus setting the groundwork for effectively preventing and managing toxocariasis.
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Affiliation(s)
- Na Wang
- Laboratory of Tropical Veterinary Medicine and Vector Biology, College of Life and Health, Hainan University, Haikou, Hainan, 570228, China; Collaborative Innovation Center of One Health, Hainan University, Haikou, Hainan, 570228, China
| | - Soben Sieng
- Laboratory of Tropical Veterinary Medicine and Vector Biology, College of Life and Health, Hainan University, Haikou, Hainan, 570228, China; Collaborative Innovation Center of One Health, Hainan University, Haikou, Hainan, 570228, China
| | - Tian Liang
- Laboratory of Tropical Veterinary Medicine and Vector Biology, College of Life and Health, Hainan University, Haikou, Hainan, 570228, China
| | - Jingyun Xu
- Laboratory of Tropical Veterinary Medicine and Vector Biology, College of Life and Health, Hainan University, Haikou, Hainan, 570228, China; Collaborative Innovation Center of One Health, Hainan University, Haikou, Hainan, 570228, China.
| | - Qian Han
- Laboratory of Tropical Veterinary Medicine and Vector Biology, College of Life and Health, Hainan University, Haikou, Hainan, 570228, China; Collaborative Innovation Center of One Health, Hainan University, Haikou, Hainan, 570228, China.
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18
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Ma Y, Su S, Fu Z, Zhou C, Qiao B, Wu Y, Yuan YJ. Convenient synthesis and delivery of a megabase-scale designer accessory chromosome empower biosynthetic capacity. Cell Res 2024; 34:309-322. [PMID: 38332200 PMCID: PMC10978979 DOI: 10.1038/s41422-024-00934-3] [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: 07/21/2023] [Accepted: 01/18/2024] [Indexed: 02/10/2024] Open
Abstract
Synthetic biology confers new functions to hosts by introducing exogenous genetic elements, yet rebuilding complex traits that are based on large-scale genetic information remains challenging. Here, we developed a CRISPR/Cas9-mediated haploidization method that bypasses the natural process of meiosis. Based on the programmed haploidization in yeast, we further developed an easy-to-use method designated HAnDy (Haploidization-based DNA Assembly and Delivery in yeast) that enables efficient assembly and delivery of large DNA, with no need for any fussy in vitro manipulations. Using HAnDy, a de novo designed 1.024 Mb synthetic accessory chromosome (synAC) encoding 542 exogenous genes was parallelly assembled and then directly transferred to six phylogenetically diverse yeasts. The synAC significantly promotes hosts' adaptations and increases the scope of the metabolic network, which allows the emergence of valuable compounds. Our approach should facilitate the assembly and delivery of large-scale DNA for expanding and deciphering complex biological functions.
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Affiliation(s)
- Yuan Ma
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin, China
| | - Shuxin Su
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin, China
| | - Zongheng Fu
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin, China
| | - Chu Zhou
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin, China
| | - Bin Qiao
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
| | - Yi Wu
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China.
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin, China.
| | - Ying-Jin Yuan
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China.
- Frontiers Research Institute for Synthetic Biology, Tianjin University, Tianjin, China.
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Ruehrmund L, Fuchs P, Bartels J, Remy R, Klemenz AC, Kemnitz N, Trefz P, Sukul P, Miekisch W, Schubert JK. Protocol for visualizing complex volatile metabolomics data in clinical setups using EDaViS software. STAR Protoc 2024; 5:102808. [PMID: 38170664 PMCID: PMC10797205 DOI: 10.1016/j.xpro.2023.102808] [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: 10/30/2023] [Revised: 11/21/2023] [Accepted: 12/15/2023] [Indexed: 01/05/2024] Open
Abstract
Here, we present a protocol for using Early Data Visualization Script, a user-friendly software tool to visualize complex volatile metabolomics data in clinical setups. We describe steps for tabulating data and adjusting visual output to visualize complex time-resolved volatile omics data using simple charts and graphs. We then demonstrate possible modifications by detailing procedures for the adaptation of four basic functions. For complete details on the use and execution of this protocol, please refer to Sukul et al. (2022)1 and Remy et al. (2022).2.
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Affiliation(s)
- Leo Ruehrmund
- Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Rostock University Medical Centre, 18057 Rostock, Germany
| | - Patricia Fuchs
- Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Rostock University Medical Centre, 18057 Rostock, Germany.
| | - Julia Bartels
- Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Rostock University Medical Centre, 18057 Rostock, Germany
| | - Rasmus Remy
- Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Rostock University Medical Centre, 18057 Rostock, Germany
| | - Ann-Christin Klemenz
- Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Rostock University Medical Centre, 18057 Rostock, Germany
| | - Nele Kemnitz
- Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Rostock University Medical Centre, 18057 Rostock, Germany
| | - Phillip Trefz
- Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Rostock University Medical Centre, 18057 Rostock, Germany
| | - Pritam Sukul
- Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Rostock University Medical Centre, 18057 Rostock, Germany
| | - Wolfram Miekisch
- Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Rostock University Medical Centre, 18057 Rostock, Germany
| | - Jochen K Schubert
- Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Rostock University Medical Centre, 18057 Rostock, Germany
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Blanco AM, Antomagesh F, Comesaña S, Soengas JL, Vijayan MM. Chronic cortisol stimulation enhances hypothalamus-specific enrichment of metabolites in the rainbow trout brain. Am J Physiol Endocrinol Metab 2024; 326:E382-E397. [PMID: 38294699 DOI: 10.1152/ajpendo.00410.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/08/2024] [Accepted: 01/24/2024] [Indexed: 02/01/2024]
Abstract
The hypothalamus is a key integrating center that is involved in the initiation of the corticosteroid stress response, and in regulating nutrient homeostasis. Although cortisol, the principal glucocorticoid in humans and teleosts, plays a central role in feeding regulation, the mechanisms are far from clear. We tested the hypothesis that the metabolic changes to cortisol exposure signal an energy excess in the hypothalamus, leading to feeding suppression during stress in fish. Rainbow trout (Oncorhynchus mykiss) were administered a slow-release cortisol implant for 3 days, and the metabolite profiles in the plasma, hypothalamus, and the rest of the brain were assessed. Also, U-13C-glucose was injected into the hypothalamus by intracerebroventricular (ICV) route, and the metabolic fate of this energy substrate was followed in the brain regions by metabolomics. Chronic cortisol treatment reduced feed intake, and this corresponded with a downregulation of the orexigenic gene agrp, and an upregulation of the anorexigenic gene cart in the hypothalamus. The U-13C-glucose-mediated metabolite profiling indicated an enhancement of glycolytic flux and tricarboxylic acid intermediates in the rest of the brain compared with the hypothalamus. There was no effect of cortisol treatment on the phosphorylation status of AMPK or mechanistic target of rapamycin in the brain, whereas several endogenous metabolites, including leucine, citrate, and lactate were enriched in the hypothalamus, suggesting a tissue-specific metabolic shift in response to cortisol stimulation. Altogether, our results suggest that the hypothalamus-specific enrichment of leucine and the metabolic fate of this amino acid, including the generation of lipid intermediates, contribute to cortisol-mediated feeding suppression in fish.NEW & NOTEWORTHY Elevated cortisol levels during stress suppress feed intake in animals. We tested whether the feed suppression is associated with cortisol-mediated alteration in hypothalamus metabolism. The brain metabolome revealed a hypothalamus-specific metabolite profile suggesting nutrient excess. Specifically, we noted the enrichment of leucine and citrate in the hypothalamus, and the upregulation of pathways involved in leucine metabolism and fatty acid synthesis. This cortisol-mediated energy substrate repartitioning may modulate the feeding/satiety centers leading to the feeding suppression.
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Affiliation(s)
- Ayelén M Blanco
- Centro de Investigación Mariña, Laboratorio de Fisioloxía Animal, Departamento de Bioloxía Funcional e Ciencias da Saúde, Facultade de Bioloxía, Universidade de Vigo, Vigo, Spain
| | | | - Sara Comesaña
- Centro de Investigación Mariña, Laboratorio de Fisioloxía Animal, Departamento de Bioloxía Funcional e Ciencias da Saúde, Facultade de Bioloxía, Universidade de Vigo, Vigo, Spain
| | - José L Soengas
- Centro de Investigación Mariña, Laboratorio de Fisioloxía Animal, Departamento de Bioloxía Funcional e Ciencias da Saúde, Facultade de Bioloxía, Universidade de Vigo, Vigo, Spain
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Gelao V, Fornasaro S, Briguglio SC, Mattiussi M, De Martin S, Astel AM, Barbieri P, Licen S. Self-Organizing Maps: An AI Tool for Identifying Unexpected Source Signatures in Non-Target Screening Analysis of Urban Wastewater by HPLC-HRMS. TOXICS 2024; 12:113. [PMID: 38393208 PMCID: PMC10891566 DOI: 10.3390/toxics12020113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 01/23/2024] [Accepted: 01/24/2024] [Indexed: 02/25/2024]
Abstract
(1) Background: Monitoring effluent in water treatment plants has a key role in identifying potential pollutants that might be released into the environment. A non-target analysis approach can be used for identifying unknown substances and source-specific multipollutant signatures. (2) Methods: Urban and industrial wastewater effluent were analyzed by HPLC-HRMS for non-target analysis. The anomalous infiltration of industrial wastewater into urban wastewater was investigated by analyzing the mass spectra data of "unknown common" compounds using principal component analysis (PCA) and the Self-Organizing Map (SOM) AI tool. The outcomes of the models were compared. (3) Results: The outlier detection was more straightforward in the SOM model than in the PCA one. The differences among the samples could not be completely perceived in the PCA model. Moreover, since PCA involves the calculation of new variables based on the original experimental ones, it is not possible to reconstruct a chromatogram that displays the recurring patterns in the urban WTP samples. This can be achieved using the SOM outcomes. (4) Conclusions: When comparing a large number of samples, the SOM AI tool is highly efficient in terms of calculation, visualization, and identifying outliers. Interpreting PCA visualization and outlier detection becomes challenging when dealing with a large sample size.
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Affiliation(s)
- Vito Gelao
- Regional Environmental Protection Agency—ARPA-FVG, Via Cairoli 14, 33057 Palmanova, Italy; (V.G.); (S.C.B.); (M.M.); (S.D.M.)
| | - Stefano Fornasaro
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via Giorgieri 1, 34127 Trieste, Italy; (S.F.); (P.B.)
| | - Sara C. Briguglio
- Regional Environmental Protection Agency—ARPA-FVG, Via Cairoli 14, 33057 Palmanova, Italy; (V.G.); (S.C.B.); (M.M.); (S.D.M.)
| | - Michele Mattiussi
- Regional Environmental Protection Agency—ARPA-FVG, Via Cairoli 14, 33057 Palmanova, Italy; (V.G.); (S.C.B.); (M.M.); (S.D.M.)
| | - Stefano De Martin
- Regional Environmental Protection Agency—ARPA-FVG, Via Cairoli 14, 33057 Palmanova, Italy; (V.G.); (S.C.B.); (M.M.); (S.D.M.)
| | - Aleksander M. Astel
- Department of Environmental Chemistry and Toxicology, Pomeranian University in Słupsk, 22a Arciszewskiego Str., 76-200 Słupsk, Poland
| | - Pierluigi Barbieri
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via Giorgieri 1, 34127 Trieste, Italy; (S.F.); (P.B.)
| | - Sabina Licen
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via Giorgieri 1, 34127 Trieste, Italy; (S.F.); (P.B.)
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Brix F, Demetrowitsch T, Jensen-Kroll J, Zacharias HU, Szymczak S, Laudes M, Schreiber S, Schwarz K. Evaluating the Effect of Data Merging and Postacquisition Normalization on Statistical Analysis of Untargeted High-Resolution Mass Spectrometry Based Urinary Metabolomics Data. Anal Chem 2024; 96:33-40. [PMID: 38113356 DOI: 10.1021/acs.analchem.3c01380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Urine is one of the most widely used biofluids in metabolomic studies because it can be collected noninvasively and is available in large quantities. However, it shows large heterogeneity in sample concentration and consequently requires normalization to reduce unwanted variation and extract meaningful biological information. Biological samples like urine are commonly measured with electrospray ionization (ESI) coupled to a mass spectrometer, producing data sets for positive and negative modes. Combining these gives a more complete picture of the total metabolites present in a sample. However, the effect of this data merging on subsequent data analysis, especially in combination with normalization, has not yet been analyzed. To address this issue, we conducted a neutral comparison study to evaluate the performance of eight postacquisition normalization methods under different data merging procedures using 1029 urine samples from the Food Chain plus (FoCus) cohort. Samples were measured with a Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR-MS). Normalization methods were evaluated by five criteria capturing the ability to remove sample concentration variation and preserve relevant biological information. Merging data after normalization was generally favorable for quality control (QC) sample similarity, sample classification, and feature selection for most of the tested normalization methods. Merging data after normalization and the usage of probabilistic quotient normalization (PQN) in a similar setting are generally recommended. Relying on a single analyte to capture sample concentration differences, like with postacquisition creatinine normalization, seems to be a less preferable approach, especially when data merging is applied.
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Affiliation(s)
- Fynn Brix
- Institute of Human Nutrition and Food Science, Kiel University, Kiel, Heinrich-Hecht-Platz 10, 24118 Kiel, Germany
| | - Tobias Demetrowitsch
- Institute of Human Nutrition and Food Science, Kiel University, Kiel, Heinrich-Hecht-Platz 10, 24118 Kiel, Germany
| | - Julia Jensen-Kroll
- Institute of Human Nutrition and Food Science, Kiel University, Kiel, Heinrich-Hecht-Platz 10, 24118 Kiel, Germany
| | - Helena U Zacharias
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, 30625 Hannover, Germany
- Department of Internal Medicine I, University Medical Centre Schleswig-Holstein, Campus Kiel, 24105 Kiel, Germany
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Campus Kiel, 24105 Kiel, Germany
| | - Silke Szymczak
- Institute of Medical Biometry and Statistics, University of Luebeck and Medical Centre Schleswig-Holstein, Campus Luebeck, 23562 Luebeck, Germany
| | - Matthias Laudes
- Department of Internal Medicine I, University Medical Centre Schleswig-Holstein, Campus Kiel, 24105 Kiel, Germany
- Institute of Diabetes and Clinical Metabolic Research, Kiel University, Düsternbrooker Weg 17, 24105 Kiel, Germany
| | - Stefan Schreiber
- Department of Internal Medicine I, University Medical Centre Schleswig-Holstein, Campus Kiel, 24105 Kiel, Germany
- Institute of Diabetes and Clinical Metabolic Research, Kiel University, Düsternbrooker Weg 17, 24105 Kiel, Germany
| | - Karin Schwarz
- Institute of Human Nutrition and Food Science, Kiel University, Kiel, Heinrich-Hecht-Platz 10, 24118 Kiel, Germany
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Wanichthanarak K, In-on A, Fan S, Fiehn O, Wangwiwatsin A, Khoomrung S. Data processing solutions to render metabolomics more quantitative: case studies in food and clinical metabolomics using Metabox 2.0. Gigascience 2024; 13:giae005. [PMID: 38488666 PMCID: PMC10941642 DOI: 10.1093/gigascience/giae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 12/22/2023] [Accepted: 02/02/2024] [Indexed: 03/18/2024] Open
Abstract
In classic semiquantitative metabolomics, metabolite intensities are affected by biological factors and other unwanted variations. A systematic evaluation of the data processing methods is crucial to identify adequate processing procedures for a given experimental setup. Current comparative studies are mostly focused on peak area data but not on absolute concentrations. In this study, we evaluated data processing methods to produce outputs that were most similar to the corresponding absolute quantified data. We examined the data distribution characteristics, fold difference patterns between 2 metabolites, and sample variance. We used 2 metabolomic datasets from a retail milk study and a lupus nephritis cohort as test cases. When studying the impact of data normalization, transformation, scaling, and combinations of these methods, we found that the cross-contribution compensating multiple standard normalization (ccmn) method, followed by square root data transformation, was most appropriate for a well-controlled study such as the milk study dataset. Regarding the lupus nephritis cohort study, only ccmn normalization could slightly improve the data quality of the noisy cohort. Since the assessment accounted for the resemblance between processed data and the corresponding absolute quantified data, our results denote a helpful guideline for processing metabolomic datasets within a similar context (food and clinical metabolomics). Finally, we introduce Metabox 2.0, which enables thorough analysis of metabolomic data, including data processing, biomarker analysis, integrative analysis, and data interpretation. It was successfully used to process and analyze the data in this study. An online web version is available at http://metsysbio.com/metabox.
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Affiliation(s)
- Kwanjeera Wanichthanarak
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Ammarin In-on
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Sili Fan
- Department of Biostatistics, University of California Davis, Davis, CA 95616, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis Genome Center, Davis, CA 95616, USA
| | - Arporn Wangwiwatsin
- Department of Systems Biosciences and Computational Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Sakda Khoomrung
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10700, Thailand
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Zhang C, Atanasov KE, Murillo E, Vives-Peris V, Zhao J, Deng C, Gómez-Cadenas A, Alcázar R. Spermine deficiency shifts the balance between jasmonic acid and salicylic acid-mediated defence responses in Arabidopsis. PLANT, CELL & ENVIRONMENT 2023; 46:3949-3970. [PMID: 37651604 DOI: 10.1111/pce.14706] [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: 05/03/2023] [Revised: 08/18/2023] [Accepted: 08/21/2023] [Indexed: 09/02/2023]
Abstract
Polyamines are small aliphatic polycations present in all living organisms. In plants, the most abundant polyamines are putrescine (Put), spermidine (Spd) and spermine (Spm). Polyamine levels change in response to different pathogens, including Pseudomonas syringae pv. tomato DC3000 (Pst DC3000). However, the regulation of polyamine metabolism and their specific contributions to defence are not fully understood. Here we report that stimulation of Put biosynthesis by Pst DC3000 is dependent on coronatine (COR) perception and jasmonic acid (JA) signalling, independently of salicylic acid (SA). Conversely, lack of Spm in spermine synthase (spms) mutant stimulated galactolipids and JA biosynthesis, and JA signalling under basal conditions and during Pst DC3000 infection, whereas compromised SA-pathway activation and defence outputs through SA-JA antagonism. The dampening of SA responses correlated with COR and Pst DC3000-inducible deregulation of ANAC019 expression and its key SA-metabolism gene targets. Spm deficiency also led to enhanced disease resistance to the necrotrophic fungal pathogen Botrytis cinerea and stimulated endoplasmic reticulum (ER) stress signalling in response to Pst DC3000. Overall, our findings provide evidence for the integration of polyamine metabolism in JA- and SA-mediated defence responses, as well as the participation of Spm in buffering ER stress during defence.
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Affiliation(s)
- Chi Zhang
- Department of Biology, Healthcare and Environment, Section of Plant Physiology, Faculty of Pharmacy and Food Sciences, Universitat de Barcelona, Barcelona, Spain
| | - Kostadin E Atanasov
- Department of Biology, Healthcare and Environment, Section of Plant Physiology, Faculty of Pharmacy and Food Sciences, Universitat de Barcelona, Barcelona, Spain
| | - Ester Murillo
- Department of Biology, Healthcare and Environment, Section of Plant Physiology, Faculty of Pharmacy and Food Sciences, Universitat de Barcelona, Barcelona, Spain
| | - Vicente Vives-Peris
- Departamento de Biología, Bioquímica y Ciencias Naturales, Universitat Jaume I, Castelló de la Plana, Spain
| | - Jiaqi Zhao
- Department of Biology, Healthcare and Environment, Section of Plant Physiology, Faculty of Pharmacy and Food Sciences, Universitat de Barcelona, Barcelona, Spain
| | - Cuiyun Deng
- Plant Synthetic Biology and Metabolic Engineering Program, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Cerdanyola, Barcelona, Spain
| | - Aurelio Gómez-Cadenas
- Departamento de Biología, Bioquímica y Ciencias Naturales, Universitat Jaume I, Castelló de la Plana, Spain
| | - Rubén Alcázar
- Department of Biology, Healthcare and Environment, Section of Plant Physiology, Faculty of Pharmacy and Food Sciences, Universitat de Barcelona, Barcelona, Spain
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25
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Huang J, Zhou F, Zhou H, Zheng X, Huo Z, Yang M, Xu Z, Liu R, Wang L, Wang X. Systematic assessment of transcriptomic and metabolic reprogramming by blue light exposure coupled with aging. PNAS NEXUS 2023; 2:pgad390. [PMID: 38059264 PMCID: PMC10697416 DOI: 10.1093/pnasnexus/pgad390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 11/06/2023] [Indexed: 12/08/2023]
Abstract
The prevalent use of light-emitting diodes (LEDs) has caused revolutionary changes in modern life, but the potential hazards to health of blue light are poorly understood. N6-methyladenosine (m6A) is the most prevalent posttranscriptional modification in eukaryotes and can modulate diverse physiological processes by regulating mRNA fate. Here, to understand the effects and molecular mechanisms of daily low-intensity blue light exposure (BLE) and ascertain whether m6A methylation plays a role in BLE-induced phenotypes, we constructed a series of Drosophila models under different durations of daily low-intensity BLE and obtained multiomics profiles. Our results revealed that BLE could induce transcriptomic, m6A epitranscriptomic, and metabolomic reprogramming in Drosophila along with aging process. Importantly, the m6A methylation sites enriched in the 5' untranslated regions (UTRs) of Drosophila transcripts showed strong age specificity and could be altered by BLE. We experimentally validated that aging-related gene Tor and circadian rhythm-related gene per were regulated by 5' UTR-enriched m6A methylation. Overall, our study provides a systematic assessment of m6A RNA methylome reprogramming by BLE and aging in Drosophila model.
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Affiliation(s)
- Jia Huang
- Department of Entomology, South China Agricultural University, Guangzhou 510642, China
| | - Fan Zhou
- Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Huanchan Zhou
- Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Xiaoqi Zheng
- Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Zhengyi Huo
- Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Meng Yang
- Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Zihe Xu
- Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Runzhou Liu
- Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Luoluo Wang
- Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences, South China Normal University, Guangzhou 510631, China
| | - Xiaoyun Wang
- Guangdong Provincial Key Laboratory of Insect Developmental Biology and Applied Technology, Institute of Insect Science and Technology, School of Life Sciences, South China Normal University, Guangzhou 510631, China
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26
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Chu Q, Wei W, Lao H, Li Y, Tan Y, Wei X, Huang B, Qin C, Tang Y. Machine learning algorithms for integrating clinical features to predict intracranial hemorrhage in patients with acute leukemia. Int J Neurosci 2023; 133:977-986. [PMID: 35156526 DOI: 10.1080/00207454.2022.2030327] [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: 04/10/2021] [Revised: 01/02/2022] [Accepted: 01/08/2022] [Indexed: 10/19/2022]
Abstract
BACKGROUND Intracranial hemorrhage (ICH) in acute leukemia (AL) patients leads to high morbidity and mortality, treatment approaches for ICH are generally ineffective. Thus, early identification of which subjects are at high risk of ICH is of key importance. Currently, machine learning can achieve well predictive capability through constructing algorithms that simultaneously exploit the information coming from clinical features. METHODS After rigid data preprocessing, 42 different clinical features from 948 AL patients were used to train different machine learning algorithms. We used the feature selection algorithms to select the top 10 features from 42 clinical features. To test the performance of the machine learning algorithms, we calculated area under the curve (AUC) values from receiver operating characteristic (ROC) curves along with 95% confidence intervals (CIs) by cross-validation. RESULTS With the 42 features, RF exhibited the best predictive power. After feature selection, the top 10 features were international normalized ratio (INR), prothrombin time (PT), creatinine (Cr), indirect bilirubin (IBIL), albumin (ALB), monocyte (MONO), platelet (PLT), lactic dehydrogenase (LDH), fibrinogen (FIB) and prealbumin (PA). Among the top 10 features, INR, PT, Cr, IBIL and ALB had high predictive performance with an AUC higher than 0.8 respectively. CONCLUSIONS The RF algorithm exhibited a higher cross-validated performance compared with the classical algorithms, and the selected important risk features should help in individualizing aggressive treatment in AL patients to prevent ICH. Efforts that will be made to test and optimize in independent samples will warrant the application of such algorithm and predictors in the future.
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Affiliation(s)
- Quanhong Chu
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Wenxin Wei
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Huan Lao
- Medical College of Guangxi University, Nanning, Guangxi, China
- School of Computer, Electronics and Information, Guangxi University, Nanning, Guangxi, China
| | - Yujian Li
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Yafu Tan
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Xiaoyong Wei
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Baozi Huang
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Chao Qin
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Yanyan Tang
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
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27
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Zhang Y, Ding X, Guo L, Zhong Y, Xie J, Xu Y, Li H, Zheng D. Comprehensive analysis of the relationship between xanthine oxidoreductase activity and chronic kidney disease. iScience 2023; 26:107332. [PMID: 37927553 PMCID: PMC10622700 DOI: 10.1016/j.isci.2023.107332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/19/2023] [Accepted: 07/05/2023] [Indexed: 11/07/2023] Open
Abstract
Chronic kidney disease (CKD) is a common disease that seriously endangers human health. However, the potential relationship between xanthine oxidoreductase (XOR) activity and CKD remains unclear. In this study, we used clinical data, CKD datasets from the Gene Expression Omnibus database, and untargeted metabolomics to explain the relationship between XOR activity and CKD. First, XOR activity showed high correlation with the biomarkers of CKD, such as serum creatinine, blood urea nitrogen, uric acid, and estimated glomerular filtration rate. Then, we used least absolute shrinkage and selection operator logical regression algorithm and random forest algorithm to screen CKD molecular markers from differentially expressed genes, and the results of qRT-PCR of XDH, KOX-1, and ROMO1 were in accordance with the results of bioinformatics analyses. In addition, untargeted metabolomics analysis revealed that the purine metabolism pathway was significantly enriched in CKD patients in the simulated models of kidney fibrosis.
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Affiliation(s)
- Yiyuan Zhang
- Department of Nephrology, The Affiliated Huai’an Hospital of Xuzhou Medical University and Huai’an Second People’s Hospital, Huai’an, China
| | - Xiaobao Ding
- Department of Nephrology, The Affiliated Huai’an Hospital of Xuzhou Medical University and Huai’an Second People’s Hospital, Huai’an, China
- Department of Pharmacology, Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, Jiangsu Province, China
| | - Lihao Guo
- Department of Nephrology, The Affiliated Huai’an Hospital of Xuzhou Medical University and Huai’an Second People’s Hospital, Huai’an, China
| | - Yanan Zhong
- Department of Nephrology, The Affiliated Huai’an Hospital of Xuzhou Medical University and Huai’an Second People’s Hospital, Huai’an, China
| | - Juan Xie
- Department of Nephrology, The Affiliated Huai’an Hospital of Xuzhou Medical University and Huai’an Second People’s Hospital, Huai’an, China
| | - Yong Xu
- Department of Nephrology, The Affiliated Huai’an Hospital of Xuzhou Medical University and Huai’an Second People’s Hospital, Huai’an, China
| | - Hailun Li
- Department of Nephrology, The Affiliated Huai’an Hospital of Xuzhou Medical University and Huai’an Second People’s Hospital, Huai’an, China
| | - Donghui Zheng
- Department of Nephrology, The Affiliated Huai’an Hospital of Xuzhou Medical University and Huai’an Second People’s Hospital, Huai’an, China
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28
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Zeng X, Li J, Chen T, Li Y, Guo S. Global metabolic profile and multiple phytometabolites in the different varieties of Gastrodia elata Blume. FRONTIERS IN PLANT SCIENCE 2023; 14:1249456. [PMID: 37915510 PMCID: PMC10616830 DOI: 10.3389/fpls.2023.1249456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 09/26/2023] [Indexed: 11/03/2023]
Abstract
Gastrodia elata Blume (Tianma in Chinese), a myco-heterotrophic orchid, is widely distributed in China. Tubers derived from this orchid are traditionally used as both medicinal and edible materials. At present, five primary varieties of G. elata are recorded in the "Flora of China." Among them, the three main varieties currently in artificial cultivation are G. elata f. elata (GR, red stem), G. elata f. glauca (GB, black stem), and G. elata f. viridis (GG, green stem). In our study, the metabolic profiles and chemical composition of these three varieties were determined via UPLC-MS/MS and HPLC-UV. In total, 11,132 metabolites were detected, from which multiple phytometabolites were identified as aromatic compounds, heteroatomic compounds, furans, carbohydrates, organic acids, and their derivatives. A number of differentially expressed metabolites (DEMs) were annotated as bioactive ingredients. Overall, parishins, vanilloloside, and gastrodin A/B in the GB group were markedly higher, whereas gastrodin, gastrol, and syringic acid were more enriched in the GG or GR groups. Moreover, HPLC fingerprint analysis also found six metabolites used as markers for the identification of Gastrodiae Rhizoma in the Chinese Pharmacopoeia, which were also typical DEMs in metabolomics. Of these, gastrodin, 4-hydroxybenzyl alcohol, citric acid, and adenosine were quantitatively detected, showing a similar result with the metabolomic data. In summary, our findings provide novel insights into the phytochemical ingredients of different G. elata varieties, highlighting diverse biological activities and healthcare value.
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Affiliation(s)
| | | | | | | | - Shunxing Guo
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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29
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Xie J, Zhou F, Ouyang L, Li Q, Rao S, Su R, Yang S, Li J, Wan X, Yan L, Liu P, Cheng H, Li L, Du G, Feng C, Fan G. Insight into the effect of a heavy metal mixture on neurological damage in rats through combined serum metabolomic and brain proteomic analyses. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 895:165009. [PMID: 37353033 DOI: 10.1016/j.scitotenv.2023.165009] [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: 12/31/2022] [Revised: 05/26/2023] [Accepted: 06/17/2023] [Indexed: 06/25/2023]
Abstract
The heavy metals lead (Pb), cadmium (Cd), and mercury (Hg) that cause neurocognitive impairment have been extensively studied. These elements typically do not exist alone in the environment; they are often found with other heavy metals and can enter the body through various routes, thereby impacting health. Our previous research showed that low Pb, Cd, and Hg levels cause neurobehavioral impairments in weaning and adult rats. However, little is known about the biomarkers and mechanisms underlying Pb, Cd, and Hg mixture-induced neurological impairments. A combined analysis of metabolomic and proteomic data may reveal heavy metal-induced alterations in metabolic and protein profiles, thereby improving our understanding of the molecular mechanisms underlying heavy metal-induced neurological impairments. Therefore, brain tissue and serum samples were collected from rats exposed to a Pb, Cd, and Hg mixture for proteomic and metabolomic analyses, respectively. The analysis revealed 363 differential proteins in the brain and 206 metabolites in serum uniquely altered in the Pb, Cd, and Hg mixture exposure group, compared to those of the control group. The main metabolic impacted pathways were unsaturated fatty acids biosynthesis, linoleic acid metabolism, phenylalanine metabolism, and tryptophan metabolism. We further identified that the levels of arachidonic acid (C20:4 n-3) and, adrenic acid (C22:4 n-3) were elevated and that kynurenic acid (KA) and quinolinic acid (QA) levels and the KA/QA ratio, were decreased in the group exposed to the Pb, Cd, and Hg mixture. A joint analysis of the proteome and metabolome showed that significantly altered proteins such as LPCAT3, SLC7A11, ASCL4, and KYAT1 may participate in the neurological impairments induced by the heavy metal mixture. Overall, we hypothesize that the dysregulation of ferroptosis and kynurenine pathways is associated with neurological damage due to chronic exposure to a heavy metal mixture.
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Affiliation(s)
- Jie Xie
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Fankun Zhou
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Lu Ouyang
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Qi Li
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Shaoqi Rao
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Rui Su
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Shuo Yang
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Jiajun Li
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Xin Wan
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Lingyu Yan
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Peishan Liu
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Hui Cheng
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Lingling Li
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Guihua Du
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Chang Feng
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China
| | - Guangqin Fan
- Department of Occupational Health and Toxicology, School of Public Health, Nanchang University, Nanchang 330006, PR China; Jiangxi Province Key Laboratory of Preventive Medicine, Nanchang University, Nanchang 330006, PR China.
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30
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Xu F, Li Q, Wang S, Dong M, Xiao G, Bai J, Wang J, Sun X. The efficacy of prevention for colon cancer based on the microbiota therapy and the antitumor mechanisms with intervention of dietary Lactobacillus. Microbiol Spectr 2023; 11:e0018923. [PMID: 37655887 PMCID: PMC10581183 DOI: 10.1128/spectrum.00189-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 07/08/2023] [Indexed: 09/02/2023] Open
Abstract
Gut microbiota and their secreted metabolites have an influence on the initiation and progression of colon cancer. Probiotics are extensively perceived as a potential microbiota-modulation strategy to promote the health of the host, while the effectiveness of preventing colon cancer based on microbiota therapy has not been confirmed, and antitumor mechanisms influenced by microbiota and their metabolites with the intervention of probiotics remain to be further investigated. In vitro, Lactobacillus (JY300-8 and JMR-01) significantly inhibited the proliferation of CT26, HT29, and HCT116 cells. Moreover, we studied the prevention and therapy efficiency of Lactobacillus and its underlying antitumor mechanism through the alteration of gut microbiota and their metabolites regulated by Lactobacillus in colon cancer models in mice. We demonstrated that the pre-administration of Lactobacillus (JY300-8 and JMR-01) for 20 days before establishing tumor models resulted in an 86.21% reduction in tumor formation rate compared to tumor control group. Subsequently, continuous oral administration of living Lactobacillus significantly suppresses tumor growth, and tumor volumes decrease by 65.2%. Microbiome and metabolome analyses reveal that Lactobacillus suppresses colonic tumorigenesis and progression through the modulation of gut microbiota homeostasis and metabolites, including the down-regulation of secondary bile acids, sphingosine 1-phosphate (S1P), and pyrimidine metabolism, as well as the production of anticarcinogenic compounds in tumor-bearing mice. Additionally, metabolome analyses of Lactobacillus (JY300-8 and JMR-01) indicate that living Lactobacillus could reduce the relative abundance of alanine and L-serine to suppress tumor progression by regulating the tumor microenvironment, including down-regulation of pyrimidine metabolism and S1P signaling in cancer. These findings provide a potential prevention strategy and therapeutic target for colon cancer through the intervention of dietary Lactobacillus. IMPORTANCE The modulation of gut microbiota and metabolites has a significant influence on the progression of colon cancer. Our research indicated that the intervention of probiotics is a potentially feasible strategy for preventing colon cancer. We have also revealed the underlying antitumor mechanism through the alteration of gut microbiota and their metabolites, which could lead to broader biomedical impacts on the prevention and therapy of colon cancer with microbiota-based therapy regulated by probiotics.
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Affiliation(s)
- Fuqiang Xu
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu, China
- College of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Qiaoqiao Li
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu, China
- College of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Shuyang Wang
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu, China
- College of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Miaoyin Dong
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu, China
- College of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Guoqing Xiao
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu, China
- College of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Jin Bai
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu, China
- College of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Junkai Wang
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu, China
| | - Xisi Sun
- Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu, China
- College of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
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Mattoli L, Gianni M, Burico M. Mass spectrometry-based metabolomic analysis as a tool for quality control of natural complex products. MASS SPECTROMETRY REVIEWS 2023; 42:1358-1396. [PMID: 35238411 DOI: 10.1002/mas.21773] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 11/16/2021] [Accepted: 02/11/2022] [Indexed: 06/07/2023]
Abstract
Metabolomics is an area of intriguing and growing interest. Since the late 1990s, when the first Omic applications appeared to study metabolite's pool ("metabolome"), to understand new aspects of the global regulation of cellular metabolism in biology, there have been many evolutions. Currently, there are many applications in different fields such as clinical, medical, agricultural, and food. In our opinion, it is clear that developments in metabolomics analysis have also been driven by advances in mass spectrometry (MS) technology. As natural complex products (NCPs) are increasingly used around the world as medicines, food supplements, and substance-based medical devices, their analysis using metabolomic approaches will help to bring more and more rigor to scientific studies and industrial production monitoring. This review is intended to emphasize the importance of metabolomics as a powerful tool for studying NCPs, by which significant advantages can be obtained in terms of elucidation of their composition, biological effects, and quality control. The different approaches of metabolomic analysis, the main and basic techniques of multivariate statistical analysis are also briefly illustrated, to allow an overview of the workflow associated with the metabolomic studies of NCPs. Therefore, various articles and reviews are illustrated and commented as examples of the application of MS-based metabolomics to NCPs.
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Affiliation(s)
- Luisa Mattoli
- Department of Metabolomics & Analytical Sciences, Aboca SpA Società Agricola, Sansepolcro, AR, Italy
| | - Mattia Gianni
- Department of Metabolomics & Analytical Sciences, Aboca SpA Società Agricola, Sansepolcro, AR, Italy
| | - Michela Burico
- Department of Metabolomics & Analytical Sciences, Aboca SpA Società Agricola, Sansepolcro, AR, Italy
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Zhou J, Pi N, Guo Y, He X, Wang J, Luo R, Wang M, Yu H. The mechanism of action of Ophiocordyceps sinensis mycelia for prevention of acute lung injury based on non-targeted serum metabolomics. PLoS One 2023; 18:e0287331. [PMID: 37327224 PMCID: PMC10275419 DOI: 10.1371/journal.pone.0287331] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 06/02/2023] [Indexed: 06/18/2023] Open
Abstract
Ophiocordyceps sinensis is a fungus with medicinal value in treating lung diseases, but no study has reported how to prevent acute lung injury using this fungus. The mice were divided into normal, model, positive control, and O. sinensis groups to observe lung histopathological sections and transmission electron microscopy, along with liquid chromatography-mass spectrometry and hematoxylin and eosin (H&E) staining to closely identify structural differences resulting from destruction between the groups. The results of the H&E staining showed that, compared with the normal group, the model group showed alveolar collapse. Compared with the model group, the infiltration of inflammatory cells in the alveolar cavity of the O. sinensis group was significantly reduced. Mitochondrial plate-like cristae were observed in type II alveolar cells of the normal group, with normal coloration of the mitochondrial matrix. Type II alveolar cells in the model group showed obvious edema. The statuses of type II alveolar cells in the O. sinensis and positive groups were similar to that in the normal group. Twenty-nine biomarkers and 10 related metabolic pathways were identified by serum metabolomics screening. The results showed that O. sinensis mycelia had a significant effect on the prevention of lipopolysaccharide-induced inflammation.
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Affiliation(s)
- Jinna Zhou
- College of Ecology and Environment Sciences, Yunnan University, Kunming, China
- School of Ecology and Environment, Tibet University, Lhasa City, China
| | - Na Pi
- Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China
| | - Yingqi Guo
- Institutional Center for Shared Technologies and Facilities of Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Xinyi He
- College of Ecology and Environment Sciences, Yunnan University, Kunming, China
| | - Jinhu Wang
- School of Ecology and Environment, Tibet University, Lhasa City, China
| | - Run Luo
- College of Ecology and Environment Sciences, Yunnan University, Kunming, China
| | - Mu Wang
- Plant Science College, Tibet Agriculture & Animal Husbandry University, Nyingchi, China
| | - Hong Yu
- College of Ecology and Environment Sciences, Yunnan University, Kunming, China
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Creydt M, Flügge F, Dammann R, Schütze B, Günther UL, Fischer M. Food Fingerprinting: LC-ESI-IM-QTOF-Based Identification of Blumeatin as a New Marker Metabolite for the Detection of Origanum majorana Admixtures to O. onites/ vulgare. Metabolites 2023; 13:metabo13050673. [PMID: 37233714 DOI: 10.3390/metabo13050673] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 05/14/2023] [Accepted: 05/15/2023] [Indexed: 05/27/2023] Open
Abstract
Oregano (Origanum vulgare and O. onites) is one of the most frequently counterfeited herbs in the world and is diluted with the leaves of a wide variety of plants. In addition to olive leaves, marjoram (O. majorana) is often used for this purpose in order to achieve a higher profit. However, apart from arbutin, no marker metabolites are known to reliably detect marjoram admixtures in oregano batches at low concentrations. In addition, arbutin is relatively widespread in the plant kingdom, which is why it is of great relevance to look for further marker metabolites in order to secure the analysis accordingly. Therefore, the aim of the present study was to use a metabolomics-based approach to identify additional marker metabolites with the aid of an ion mobility mass spectrometry instrument. The focus of the analysis was on the detection of non-polar metabolites, as this study was preceded by nuclear magnetic resonance spectroscopic investigations of the same samples based mainly on the detection of polar analytes. Using the MS-based approach, numerous marjoram specific features could be detected in admixtures of marjoram >10% in oregano. However, only one feature was detectable in admixtures of >5% marjoram. This feature was identified as blumeatin, which belongs to the class of flavonoid compounds. Initially, blumeatin was identified based on MS/MS spectra and collision cross section values using a database search. In addition, the identification of blumeatin was confirmed by a reference standard. Moreover, dried leaves of olive, myrtle, thyme, sage and peppermint, which are also known to be used to adulterate oregano, were measured. Blumeatin could not be detected in these plants, so this substance can be considered as an excellent marker compound for the detection of marjoram admixtures.
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Affiliation(s)
- Marina Creydt
- Institute of Food Chemistry, Hamburg School of Food Science, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany
- Cluster of Excellence, Understanding Written Artefacts, University of Hamburg, Warburgstraße 26, 20354 Hamburg, Germany
| | - Friedemann Flügge
- Institute of Chemistry and Metabolomics, University of Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany
- LADR GmbH Medizinisches Versorgungszentrum Dr. Kramer & Kollegen, Lauenburger Straße 67, 21502 Geesthacht, Germany
| | - Robin Dammann
- Institute of Food Chemistry, Hamburg School of Food Science, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany
| | - Burkhard Schütze
- LADR GmbH Medizinisches Versorgungszentrum Dr. Kramer & Kollegen, Lauenburger Straße 67, 21502 Geesthacht, Germany
| | - Ulrich L Günther
- Institute of Chemistry and Metabolomics, University of Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany
| | - Markus Fischer
- Institute of Food Chemistry, Hamburg School of Food Science, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany
- Cluster of Excellence, Understanding Written Artefacts, University of Hamburg, Warburgstraße 26, 20354 Hamburg, Germany
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Liu X, Du Y, Na X, Wang M, Qu Y, Ge L, Wang Y, Gao L, Bai W, Bi Y, Zhou L. Integrative transcriptome and metabolome revealed the molecular mechanism of Bacillus megaterium BT22-mediated growth promotion in Arabidopsis thaliana. JOURNAL OF PLANT PHYSIOLOGY 2023; 285:153995. [PMID: 37163868 DOI: 10.1016/j.jplph.2023.153995] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/06/2023] [Accepted: 04/20/2023] [Indexed: 05/12/2023]
Abstract
Plant growth-promoting rhizobacteria (PGPR) can promote plant growth and protect plants from pathogens, which contributes to sustainable agricultural development. Several studies have reported their beneficial characteristics in facilitating plant growth and development and enhancing plant stress resistance through different mechanisms. However, there is still a challenge to study the molecular mechanism of plant response to PGPR. We integrated the transcriptome and metabolome of Arabidopsis thaliana (Arabidopsis) to understand its responses to the inoculation with an isolated PGPR strain (BT22) of Bacillus megaterium. Fresh shoot weight, dry shoot weight and leaf number of Arabidopsis were increased by BT22 treatment, showing a positive growth-promoting effect. According multi-omics analysis, 878 differentially expressed genes (296 up-regulated, 582 down-regulated) and 139 differentially expressed metabolites (66 up-regulated, 73 down-regulated) response to BT22 inoculation. GO enrichment results indicate that the up-regulated genes mainly enriched in the regulation of growth and auxin response pathways. In contrast, the down-regulated genes mainly enriched in wounding response, jasmonic acid and ethylene pathways. BT22 inoculation regulated plant hormone signal transduction of Arabidopsis, including auxin and cytokinin response genes AUX/IAA, SAUR, and A-ARR related to cell enlargement and cell division. The contents of nine flavonoids and seven phenylpropanoid metabolites were increased, which help to induce systemic resistance in plants. These results suggest that BT22 promoted Arabidopsis growth by regulating plant hormone homeostasis and inducing metabolome reprogramming.
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Affiliation(s)
- Xiao Liu
- Biophysics Group, Biomedical Center, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, 730000, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yan Du
- Biophysics Group, Biomedical Center, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, 730000, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaofan Na
- College of Life Science, Lanzhou University, Lanzhou, 730000, China
| | - Man Wang
- College of Life Science and Engineering, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Ying Qu
- Biophysics Group, Biomedical Center, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, 730000, China; University of Chinese Academy of Sciences, Beijing, 100049, China; Kejin Innovation Institute of Heavy Ion Beam Biological Industry, Baiyin, 730900, China
| | - Linghui Ge
- College of Pharmacy, Gansu University of Chinese Medicine, Lanzhou, 730000, China
| | - Yuanmeng Wang
- College of Pharmacy, Gansu University of Chinese Medicine, Lanzhou, 730000, China
| | - Linqi Gao
- Lueyang County Jinxiu Agricultural Development Co., Ltd, Lueyang, Hanzhong, 724300, China
| | - Wenke Bai
- Lueyang County Jinxiu Agricultural Development Co., Ltd, Lueyang, Hanzhong, 724300, China
| | - Yurong Bi
- College of Life Science, Lanzhou University, Lanzhou, 730000, China
| | - Libin Zhou
- Biophysics Group, Biomedical Center, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, 730000, China; University of Chinese Academy of Sciences, Beijing, 100049, China; Kejin Innovation Institute of Heavy Ion Beam Biological Industry, Baiyin, 730900, China.
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Liao XX, Hu K, Xie XH, Wen YL, Wang R, Hu ZW, Zhou YL, Li JJ, Wu MK, Yu JX, Chen JW, Ren P, Wu XY, Zhou JJ. Banxia Xiexin decoction alleviates AS co-depression disease by regulating the gut microbiome-lipid metabolic axis. JOURNAL OF ETHNOPHARMACOLOGY 2023; 313:116468. [PMID: 37044233 DOI: 10.1016/j.jep.2023.116468] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 04/02/2023] [Accepted: 04/04/2023] [Indexed: 05/08/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Banxia Xiexin decoction (BXD) is a classic Chinese herbal formulation consisting of 7 herbs including Pinelliae Rhizoma, Scutellariae Radix, Zingiberis Rhizoma, Ginseng Radix, Glycyrrhizae Radix, Coptidis Rhizoma, and Jujubae Fructus, which can exert effects on lowering lipids and alleviating depressive mood disorders via affecting gastrointestinal tract. AIM OF THE STUDY The pathogenesis of atherosclerosis (AS) co-depression disease has not been well studied, and the current clinical treatment strategies are not satisfactory. As a result, it is critical to find novel methods of treatment. Based on the hypothesis that the gut microbiome may promote the development of AS co-depression disease by regulating host lipid metabolism, this study sought to evaluate the effectiveness and action mechanism of BXD in regulation of the gut microbiome via an intervention in AS co-depression mice. MATERIALS AND METHODS To determine the primary constituents of BXD, UPLC-Q/TOF-MS analysis was carried out. Sixteen C56BL/6 mice were fed normal chow as a control group; 64 ApoE-/- mice were randomized into four groups (model group and three treatment groups) and fed high-fat chow combined with daily bind stimulation for sixteen weeks to develop the AS co-depression mouse model and were administered saline or low, medium or high concentrations of BXD during the experimental modeling period. The antidepressant efficacy of BXD was examined by weighing, a sucrose preference test, an open field test, and a tail suspension experiment. The effectiveness of BXD as an anti-AS treatment was evaluated by means of biochemical indices, the HE staining method, and the Oil red O staining method. The impacts of BXD on the gut microbiome structure and brain (hippocampus and prefrontal cortex tissue) lipids in mice with the AS co-depression model were examined by 16S rDNA sequencing combined with lipidomics analysis. RESULTS The main components of BXD include baicalin, berberine, ginsenoside Rb1, and 18 other substances. BXD could improve depression-like behavioral characteristics and AS-related indices in AS co-depression mice; BXD could regulate the abundance of some flora (phylum level: reduced abundance of Proteobacteria and Deferribacteres; genus level: reduced abundance of Clostridium_IV, Helicobacter, and Pseudoflavonifractor, Acetatifactor, Oscillibacter, which were significantly different). The lipidomics analysis showed that the differential lipids between the model and gavaged high-dose BXD (BXH) groups were enriched in glycerophospholipid metabolism, and lysophosphatidylcholine (LPC(20:3)(rep)(rep)) in the hippocampus and LPC(20:4)(rep) in the prefrontal cortex both showed downregulation in BXH. The correlation analysis illustrated that the screened differential lipids were mainly linked to Deferribacteres and Actinobacteria. CONCLUSION BXD may exert an anti-AS co-depression therapeutic effect by modulating the abundance of some flora and thus intervening in peripheral lipid and brain lipid metabolism (via downregulation of LPC levels).
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Affiliation(s)
- Xing-Xing Liao
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Ke Hu
- Department of Rehabilitation Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210008, China
| | - Xin-Hua Xie
- Key Laboratory of Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases of Ministry of Education, Gannan Medical University, Ganzhou, 341000, China
| | - You-Liang Wen
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Rui Wang
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Zi-Wei Hu
- Department of Rehabilitation, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China
| | - Yu-Long Zhou
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Jia-Jun Li
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Ming-Kun Wu
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Jing-Xuan Yu
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Jia-Wei Chen
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Peng Ren
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China
| | - Xiao-Yun Wu
- School of Basic Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China.
| | - Jun-Jie Zhou
- School of Rehabilitation Medicine, Gannan Medical University, Ganzhou, Jiangxi, 341000, China; Key Laboratory of Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases of Ministry of Education, Gannan Medical University, Ganzhou, 341000, China.
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Sun X, Feng H, Luo J, Lin L, Zhang H, Duan Y, Liu F, Zhang K, Wang B, Li D, Hu Y, Zhu Z. A novel N-arachidonoyl-l-alanine-catabolizing strain of Serratia marcescens for the bioremediation of Cd and Cr co-contamination. ENVIRONMENTAL RESEARCH 2023; 222:115376. [PMID: 36736755 DOI: 10.1016/j.envres.2023.115376] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 01/03/2023] [Accepted: 01/25/2023] [Indexed: 06/18/2023]
Abstract
Cadmium (Cd) and chromium (Cr) are widespread contaminants with a high risk to the environment and humans. Herein we isolated a novel strain of Serratia marcescens, namely strain S27, from soil co-contaminated with Cd and Cr. This strain showed strong resistance to Cd as well as Cr. S27 cells demonstrated Cd adsorption rate of 45.8% and Cr reduction capacity of 84.4% under optimal growth conditions (i.e., 30 °C, 200 rpm, and pH 7.5). Microscopic characterization of S27 cells revealed the importance of the functional groups C-O-C, C-H-O, C-C, C-H, and -OH, and also indicated that Cr reduction occurred on bacterial cell membrane. Cd(II) and Cr(VI) bioaccumulation on S27 cell surface was mainly in the form of Cd(OH)2 and Cr2O3, respectively. Further, metabolomic analyses revealed that N-arachidonoyl-l-alanine was the key metabolite that promoted Cd and Cr complexation by S27; it primarily promotes γ-linolenic acid (GLA) metabolism, producing siderophores and coordinating with organic acids to enhance metal bioavailability. To summarize, our results suggest that S27 is promising for the bioremediation of environments contaminated with Cd and Cr in tropical regions.
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Affiliation(s)
- Xiaoyan Sun
- College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Huiping Feng
- College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Jialiang Luo
- College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Li Lin
- Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, 53007, China
| | - Haixiang Zhang
- College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Yali Duan
- College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Fan Liu
- College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Kailu Zhang
- College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Baijie Wang
- College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Dong Li
- Key Laboratory of Agro-Forestry Environmental Processes and Ecological, Regulation of Hainan Province/Center for Eco-Environmental Restoration, Engineering of Hainan Province/School of Ecology & Environment/State Key, Laboratory of Marine Resource Utilization in South China Sea/Key Laboratory for Environmental Toxicology of Haikou, Hainan University, Haikou, Hainan, 570228, China.
| | - Yueming Hu
- College of Tropical Crops, Hainan University, Haikou, 570228, China
| | - Zhiqiang Zhu
- College of Tropical Crops, Hainan University, Haikou, 570228, China.
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Rischke S, Hahnefeld L, Burla B, Behrens F, Gurke R, Garrett TJ. Small molecule biomarker discovery: Proposed workflow for LC-MS-based clinical research projects. J Mass Spectrom Adv Clin Lab 2023; 28:47-55. [PMID: 36872952 PMCID: PMC9982001 DOI: 10.1016/j.jmsacl.2023.02.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 02/14/2023] [Accepted: 02/14/2023] [Indexed: 02/19/2023] Open
Abstract
Mass spectrometry focusing on small endogenous molecules has become an integral part of biomarker discovery in the pursuit of an in-depth understanding of the pathophysiology of various diseases, ultimately enabling the application of personalized medicine. While LC-MS methods allow researchers to gather vast amounts of data from hundreds or thousands of samples, the successful execution of a study as part of clinical research also requires knowledge transfer with clinicians, involvement of data scientists, and interactions with various stakeholders. The initial planning phase of a clinical research project involves specifying the scope and design, and engaging relevant experts from different fields. Enrolling subjects and designing trials rely largely on the overall objective of the study and epidemiological considerations, while proper pre-analytical sample handling has immediate implications on the quality of analytical data. Subsequent LC-MS measurements may be conducted in a targeted, semi-targeted, or non-targeted manner, resulting in datasets of varying size and accuracy. Data processing further enhances the quality of data and is a prerequisite for in-silico analysis. Nowadays, the evaluation of such complex datasets relies on a mix of classical statistics and machine learning applications, in combination with other tools, such as pathway analysis and gene set enrichment. Finally, results must be validated before biomarkers can be used as prognostic or diagnostic decision-making tools. Throughout the study, quality control measures should be employed to enhance the reliability of data and increase confidence in the results. The aim of this graphical review is to provide an overview of the steps to be taken when conducting an LC-MS-based clinical research project to search for small molecule biomarkers.
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Key Words
- (U)HPLC (Ultra-), High pressure liquid chromatography
- Biomarker Discovery Study
- HILIC, Hydrophilic interaction liquid chromatography
- HRMS, High resolution mass spectrometry
- LC-MS, Liquid chromatography – mass spectrometry
- LC-MS-Based Clinical Research
- Lipidomics
- MRM, Multiple reaction monitoring
- Metabolomics
- PCA, Principal component analysis
- QA, Quality assurance
- QC, Quality control
- RF, Random Forest
- RP, Reversed phase
- SVA, Support vector machine
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Affiliation(s)
- S Rischke
- pharmazentrum frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - L Hahnefeld
- pharmazentrum frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany.,Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - B Burla
- Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - F Behrens
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany.,Division of Rheumatology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - R Gurke
- pharmazentrum frankfurt/ZAFES, Institute of Clinical Pharmacology, Johann Wolfgang Goethe University, Theodor Stern-Kai 7, 60590 Frankfurt am Main, Germany.,Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, and Fraunhofer Cluster of Excellence for Immune Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany
| | - T J Garrett
- Department of Pathology, Immunology and Laboratory Medicine and Southeast Center for Integrated Metabolomics, University of Florida, Gainesville, FL 32611, USA
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Bile metabolites as diagnostic biomarkers for perihilar cholangiocarcinoma. Sci Rep 2023; 13:3177. [PMID: 36823159 PMCID: PMC9950048 DOI: 10.1038/s41598-023-27603-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 01/04/2023] [Indexed: 02/25/2023] Open
Abstract
It is difficult to directly obtain pathological diagnosis of perihilar cholangiocarcinoma (pCCA). Analysis of bile in the pCCA microenvironment, based on metabolomics and statistical methods, can help in clinical diagnosis. Clinical information, bile samples, blood liver function, blood CA199, CEA, and other indicators were collected from 33 patients with pCCA and 16 patients with gallstones. Bile samples were analyzed using untargeted metabolomics methods. A combination of multivariate and univariate analyses were used to screen for potential differential metabolites Through Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and differential metabolite remodeling, we explored changes in the pCCA pathway and potential therapeutic targets. There were significant differences in patient blood TBIL, ALT, AST, TBA, CA19-9, and CEA indices (p < 0.05, |log2(fc)| ≥ 1) between two groups. A significant correlation was found between these different indicators by Spearman's analysis. The clinical parameters were correlated with mass-to-charge ratios of 305 (Positive Ion Mode, POS) and 246 (Negative Ion Mode, NEG) in the metabolic group (|r| ≥ 0.7, P ≤ 10-7). The result of this study indicated that bile untargeted metabolomics combined with statistical analysis techniques may be used for diagnose and treatment of pCCA.
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Metabolic landscape dysregulation in bronchoalveolar lavage fluid of checkpoint inhibitor pneumonitis. Clin Immunol 2023; 247:109230. [PMID: 36646189 DOI: 10.1016/j.clim.2023.109230] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 01/03/2023] [Accepted: 01/11/2023] [Indexed: 01/15/2023]
Abstract
BACKGROUND Checkpoint inhibitor pneumonitis (CIP) is a potentially fatal adverse event resulting from immunotherapy in patients with malignant tumors. However, the pathogenesis of CIP remains poorly understood. METHODS We collected bronchoalveolar lavage fluid (BALF) from cohorts of patients with CIP, new-onset lung cancer (LC), and idiopathic pulmonary fibrosis (IPF). Non-targeted metabolomics analysis was conducted to analyze metabolic signatures. Flow cytometry was used to evaluate immune cell subsets. RESULTS Lymphocytes were predominant in the BALF of patients with CIP. A total of 903 metabolites were identified, among which lipid compounds were the most abundant. In a comparison between patients with CIP and LC, enrichment analysis of the altered metabolites showed suppressed amino sugar metabolism, and spermidine and spermine biosynthesis in the CIP group. Metabolism of alpha linolenic acid, linoleic acid, and their fatty acid derivatives was enriched in the CIP group relative to the IPF group. The twelve metabolites found to be enriched in the CIP group were positively correlated with the proportion of CD8+ T cells. One cluster of BALF metabolites, 57.14% of which were lipid molecules, was inversely correlated with the proportion of natural killer cells. CONCLUSIONS In this study, the metabolomic landscape of BALF in patients with CIP was determined. We elucidated suppressed tumor metabolic signatures, enhanced pulmonary inflammatory signaling, and the characteristics of responsible immune cells, which helps to understand the pathogenesis of CIP.
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Chen J, Wu F, Wang H, Guo C, Zhang W, Luo P, Zhou J, Hao W, Yang G, Huang J. Identification of key taste components in Baccaurea ramiflora Lour. fruit using non-targeted metabolomics. FOOD SCIENCE AND HUMAN WELLNESS 2023. [DOI: 10.1016/j.fshw.2022.07.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Stancliffe E, Schwaiger-Haber M, Sindelar M, Murphy MJ, Soerensen M, Patti GJ. An Untargeted Metabolomics Workflow that Scales to Thousands of Samples for Population-Based Studies. Anal Chem 2022; 94:17370-17378. [PMID: 36475608 PMCID: PMC11018270 DOI: 10.1021/acs.analchem.2c01270] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The success of precision medicine relies upon collecting data from many individuals at the population level. Although advancing technologies have made such large-scale studies increasingly feasible in some disciplines such as genomics, the standard workflows currently implemented in untargeted metabolomics were developed for small sample numbers and are limited by the processing of liquid chromatography/mass spectrometry data. Here we present an untargeted metabolomics workflow that is designed to support large-scale projects with thousands of biospecimens. Our strategy is to first evaluate a reference sample created by pooling aliquots of biospecimens from the cohort. The reference sample captures the chemical complexity of the biological matrix in a small number of analytical runs, which can subsequently be processed with conventional software such as XCMS. Although this generates thousands of so-called features, most do not correspond to unique compounds from the samples and can be filtered with established informatics tools. The features remaining represent a comprehensive set of biologically relevant reference chemicals that can then be extracted from the entire cohort's raw data on the basis of m/z values and retention times by using Skyline. To demonstrate applicability to large cohorts, we evaluated >2000 human plasma samples with our workflow. We focused our analysis on 360 identified compounds, but we also profiled >3000 unknowns from the plasma samples. As part of our workflow, we tested 14 different computational approaches for batch correction and found that a random forest-based approach outperformed the others. The corrected data revealed distinct profiles that were associated with the geographic location of participants.
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Affiliation(s)
- Ethan Stancliffe
- Department of Chemistry, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Center for Metabolomics and Isotope Tracing at Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Michaela Schwaiger-Haber
- Department of Chemistry, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Center for Metabolomics and Isotope Tracing at Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Miriam Sindelar
- Department of Chemistry, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Center for Metabolomics and Isotope Tracing at Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Matthew J. Murphy
- Department of Chemistry, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Center for Metabolomics and Isotope Tracing at Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Mette Soerensen
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Gary J. Patti
- Department of Chemistry, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Center for Metabolomics and Isotope Tracing at Washington University in St. Louis, St. Louis, Missouri 63130, United States
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, Missouri 63130, United States
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Zhang R, Wang J, Xia R, Li D, Wang F. Antioxidant processes involving epicatechin decreased symptoms of pine wilt disease. FRONTIERS IN PLANT SCIENCE 2022; 13:1015970. [PMID: 36570913 PMCID: PMC9780601 DOI: 10.3389/fpls.2022.1015970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 11/23/2022] [Indexed: 06/17/2023]
Abstract
Since the pine wood nematode (PWN, Bursaphelenchus xylophilus) invasion of Northeast China, both symptomatic and asymptomatic PWN carriers have been found. Asymptomatic PWN carriers, which are more dangerous than symptomatic carriers, constitute a source of infection in the following spring. The simultaneous presence of symptomatic and asymptomatic PWN carriers indicates that Pinus koraiensis has different tolerance levels to PWN. In this study, validity of susceptibility testing discovered differential types of P. koraiensis including Latent Reservoirs, Low Susceptibles, High Susceptibles and Bell Ringers. Among those types, the Low Susceptibles and Latent Reservoirs were asymptomatic PWN carriers, and Latent Reservoirs were the most dangerous. Transcriptome and metabolomic data showed that 5 genes (3 ans and 2 anr gene) involved in the epicatechin (EC) synthesis pathway were significantly upregulated, which increased the content of EC antioxidants in Latent Reservoirs. Hydrogen peroxide (H2O2) staining and content determination showed that the hypersensitive response (HR) and H2O2, which functions as a signaling molecule in systemic acquired resistance, decreased in Latent Reservoirs. However, low contents of EC and high contents of H2O2 were found in the High Susceptibles of P. koraiensis. RT-PCR results showed that the expression of ans and anr was upregulated together only in Latent Reservoirs. These results show that the susceptibility of P. koraiensis to PWN differed among different individuals, although no resistant individuals were found. Latent Reservoirs, in which more PWNs resided without visible symptoms via prolonged incubation period, inhibited the symptoms caused by H2O2 because of increased contents of the EC antioxidants.
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Affiliation(s)
- Ruizhi Zhang
- Key Laboratory of Alien Forest Pest Detection and Control-Heilongjiang Province, School of Forestry, Northeast Forestry University, Harbin, China
| | - Jianan Wang
- Key Laboratory of Alien Forest Pest Detection and Control-Heilongjiang Province, School of Forestry, Northeast Forestry University, Harbin, China
| | - Rui Xia
- Key Laboratory of Alien Forest Pest Detection and Control-Heilongjiang Province, School of Forestry, Northeast Forestry University, Harbin, China
| | - Danlei Li
- Key Laboratory of Alien Forest Pest Detection and Control-Heilongjiang Province, School of Forestry, Northeast Forestry University, Harbin, China
| | - Feng Wang
- Key Laboratory of Alien Forest Pest Detection and Control-Heilongjiang Province, School of Forestry, Northeast Forestry University, Harbin, China
- Liaoning Provincial Key Laboratory of Dangerous Forest Pest Management and Control, Liaoning forestry and grassland Bureau, Fushun, China
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Zeng S, Peng O, Hu F, Xia Y, Geng R, Zhao Y, He Y, Xu Q, Xue C, Cao Y, Zhang H. Metabolomic analysis of porcine intestinal epithelial cells during swine acute diarrhea syndrome coronavirus infection. Front Cell Infect Microbiol 2022; 12:1079297. [PMID: 36530441 PMCID: PMC9751206 DOI: 10.3389/fcimb.2022.1079297] [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: 10/25/2022] [Accepted: 11/15/2022] [Indexed: 12/04/2022] Open
Abstract
Swine acute diarrhea syndrome coronavirus (SADS-CoV) is an enveloped, positive single-stranded RNA virus belonging to Coronaviridae family, Orthocoronavirinae subfamily, Alphacoronavirus genus. As one of the main causes of swine diarrhea, SADS-CoV has brought huge losses to the pig industry. Although we have a basic understanding of SADS-CoV, the research on the pathogenicity and interactions between host and virus are still limited, especially the metabolic changes induced by SADS-CoV infection. Here, we utilized a combination of untargeted metabolomics and lipomics to analyze the metabolic alteration in SADS-CoV infected cells. Significant changes were observed in 1257 of 2225 metabolites identified in untargeted metabolomics, while the number of lipomics was 435 out of 868. Metabolic pathway enrichment analysis showed that amino acid metabolism, tricarboxylic acid (TCA) cycle and ferroptosis were disrupted during viral infection, suggesting that these metabolic pathways may partake in pathological processes related to SADS-CoV pathogenesis. Collectively, our findings gain insights into the cellular metabolic disorder during SADS-CoV infection, offer a valuable resource for further exploration of the relationship between virus and host metabolic activities, and provide potential targets for the development of antiviral drugs.
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Affiliation(s)
- Siying Zeng
- State Key Laboratory of Biocontrol, Life Sciences School, Sun Yat‐sen University, Guangzhou, China
| | - Ouyang Peng
- State Key Laboratory of Biocontrol, Life Sciences School, Sun Yat‐sen University, Guangzhou, China
| | - Fangyu Hu
- State Key Laboratory of Biocontrol, Life Sciences School, Sun Yat‐sen University, Guangzhou, China
| | - Yu Xia
- State Key Laboratory of Biocontrol, Life Sciences School, Sun Yat‐sen University, Guangzhou, China
| | - Rui Geng
- State Key Laboratory of Biocontrol, Life Sciences School, Sun Yat‐sen University, Guangzhou, China
| | - Yan Zhao
- State Key Laboratory of Biocontrol, Life Sciences School, Sun Yat‐sen University, Guangzhou, China
| | - Yihong He
- State Key Laboratory of Biocontrol, Life Sciences School, Sun Yat‐sen University, Guangzhou, China
| | - Qiuping Xu
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat‐sen University, Guangzhou, China
| | - Chunyi Xue
- State Key Laboratory of Biocontrol, Life Sciences School, Sun Yat‐sen University, Guangzhou, China
| | - Yongchang Cao
- State Key Laboratory of Biocontrol, Life Sciences School, Sun Yat‐sen University, Guangzhou, China
| | - Hao Zhang
- State Key Laboratory of Biocontrol, Life Sciences School, Sun Yat‐sen University, Guangzhou, China,*Correspondence: Hao Zhang,
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YANG XM, BO YK, YANG D, ZHAO GJ, DONG ZQ, KANG SS, ZHAO LS, AN M. Investigation of the mechanism of traditional Mongolian medicine Gurigumu-13 pill for treating acetaminophen-induced liver injury using a network pharmacology and metabolomics approach. CHINESE JOURNAL OF ANALYTICAL CHEMISTRY 2022. [DOI: 10.1016/j.cjac.2022.100156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Wang Z, Liu J, White JF, Li C. Epichloë bromicola from wild barley improves salt-tolerance of cultivated barley by altering physiological responses to salt stress. Front Microbiol 2022; 13:1044735. [PMID: 36504776 PMCID: PMC9730248 DOI: 10.3389/fmicb.2022.1044735] [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: 09/15/2022] [Accepted: 11/02/2022] [Indexed: 11/25/2022] Open
Abstract
Introduction Epichloë bromicola is a cultivable fungal endophyte that lives in symbiosis with wild barley (Hordeum brevisubulatum) to which it confers salt tolerance. This study tested the hypothesis that E. bromicola derived from wild barley has the potential to increase salt tolerance in cultivated barley under salt stress. Methods To test this hypothesis, the growth response, physiological parameters, and metabolic profiles of barley plants inoculated with E. bromicola (E+) and those not inoculated with E. bromicola (E-) were compared under salt stress. Results Compared with E- barley plants, E+ barley plants had significantly increased plant height, shoot biomass, total biomass, chlorophyll content, osmotic synthesis, and accumulation of stress adaptation metabolites. E. bromicola increased the salt stress tolerance of cultivated barley, and the positive effects correlated with different salt stress conditions. Discussion These results suggest that E. bromicola has promising potential for enhancing the salt tolerance of barley. New insights into the mechanisms underlying this barley-fungal endophyte association are provided, and interesting questions regarding the role of E. bromicola in fungus-enhanced tolerance to salt stress in this symbiosis are raised.
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Affiliation(s)
- Zhengfeng Wang
- Economic Crops and Malt Barley Research Institute, Gansu Academy of Agricultural Science, Lanzhou, China
| | - Jing Liu
- State Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, Gansu Tech Innovation Center of Western China Grassland Industry, Centre for Grassland Microbiome, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, China
| | - James F. White
- Department of Plant Biology, Rutgers University, New Brunswick, NJ, United States
| | - Chunjie Li
- Grassland Research Center of National Forestry and Grassland Administration, Chinese Academy of Forestry Sciences, Beijing, China,*Correspondence: Chunjie Li
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He W, Cardoso AS, Hyde RM, Green MJ, Scurr DJ, Griffiths RL, Randall LV, Kim DH. Metabolic alterations in dairy cattle with lameness revealed by untargeted metabolomics of dried milk spots using direct infusion-tandem mass spectrometry and the triangulation of multiple machine learning models. Analyst 2022; 147:5537-5545. [PMID: 36341756 PMCID: PMC9678129 DOI: 10.1039/d2an01520j] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/18/2022] [Indexed: 07/29/2023]
Abstract
Lameness is a major challenge in the dairy cattle industry in terms of animal welfare and economic implications. Better understanding of metabolic alteration associated with lameness could lead to early diagnosis and effective treatment, there-fore reducing its prevalence. To determine whether metabolic signatures associated with lameness could be discovered with untargeted metabolomics, we developed a novel workflow using direct infusion-tandem mass spectrometry to rapidly analyse (2 min per sample) dried milk spots (DMS) that were stored on commercially available Whatman® FTA® DMPK cards for a prolonged period (8 and 16 days). An orthogonal partial least squares-discriminant analysis (OPLS-DA) method validated by triangulation of multiple machine learning (ML) models and stability selection was employed to reliably identify important discriminative metabolites. With this approach, we were able to differentiate between lame and healthy cows based on a set of lipid molecules and several small metabolites. Among the discriminative molecules, we identified phosphatidylglycerol (PG 35:4) as the strongest and most sensitive lameness indicator based on stability selection. Overall, this untargeted metabolomics workflow is found to be a fast, robust, and discriminating method for determining lameness in DMS samples. The DMS cards can be potentially used as a convenient and cost-effective sample matrix for larger scale research and future routine screening for lameness.
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Affiliation(s)
- Wenshi He
- Centre for Analytical Bioscience, Advanced Materials & Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK.
| | - Ana S Cardoso
- School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire, LE12 5RD, UK
| | - Robert M Hyde
- School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire, LE12 5RD, UK
| | - Martin J Green
- School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire, LE12 5RD, UK
| | - David J Scurr
- Centre for Analytical Bioscience, Advanced Materials & Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK.
| | - Rian L Griffiths
- Centre for Analytical Bioscience, Advanced Materials & Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK.
| | - Laura V Randall
- School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire, LE12 5RD, UK
| | - Dong-Hyun Kim
- Centre for Analytical Bioscience, Advanced Materials & Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK.
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Deng P, Liang H, Wang S, Hao R, Han J, Sun X, Pan X, Li D, Wu Y, Huang Z, Xue J, Chen Z. Combined metabolomics and network pharmacology to elucidate the mechanisms of Dracorhodin Perchlorate in treating diabetic foot ulcer rats. Front Pharmacol 2022; 13:1038656. [PMID: 36532755 PMCID: PMC9752146 DOI: 10.3389/fphar.2022.1038656] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 10/31/2022] [Indexed: 10/10/2023] Open
Abstract
Background: Diabetic foot ulcer (DFU) is a severe chronic complication of diabetes, that can result in disability or death. Dracorhodin Perchlorate (DP) is effective for treating DFU, but the potential mechanisms need to be investigated. We aimed to explore the mechanisms underlying the acceleration of wound healing in DFU by the topical application of DP through the combination of metabolomics and network pharmacology. Methods: A DFU rat model was established, and the rate of ulcer wound healing was assessed. Different metabolites were found in the skin tissues of each group, and MetaboAnalyst was performed to analyse metabolic pathways. The candidate targets of DP in the treatment of DFU were screened using network pharmacology. Cytoscape was applied to construct an integrated network of metabolomics and network pharmacology. Moreover, the obtained hub targets were validated using molecular docking. After the topical application of DP, blood glucose, the rate of wound healing and pro-inflammatory cytokine levels were assessed. Results: The levels of IL-1, hs-CRP and TNF-α of the Adm group were significantly downregulated. A total of 114 metabolites were identified. These could be important to the therapeutic effects of DP in the treatment of DFU. Based on the network pharmacology, seven hub genes were found, which were partially consistent with the metabolomics results. We focused on four hub targets by further integrated analysis, namely, PAH, GSTM1, DHFR and CAT, and the crucial metabolites and pathways. Molecular docking results demonstrated that DP was well combined with the hub targets. Conclusion: Our research based on metabolomics and network pharmacology demonstrated that DP improves wound healing in DFU through multiple targets and pathways, and it can potentially be used for DFU treatment.
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Affiliation(s)
- Pin Deng
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Huan Liang
- Department of Orthopedics, Beijing Longfu Hospital, Beijing, China
| | - Shulong Wang
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Ruinan Hao
- State Key Laboratory of Organic-Inorganic Composites, Beijing University of Chemical Technology, Beijing, China
- Beijing Laboratory of Biomedical Materials, Beijing University of Chemical Technology, Beijing, China
| | - Jinglu Han
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Xiaojie Sun
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Xuyue Pan
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Dongxiao Li
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Yinwen Wu
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
| | - Zhichao Huang
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Jiajia Xue
- State Key Laboratory of Organic-Inorganic Composites, Beijing University of Chemical Technology, Beijing, China
- Beijing Laboratory of Biomedical Materials, Beijing University of Chemical Technology, Beijing, China
| | - Zhaojun Chen
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
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Li G, Jian T, Liu X, Lv Q, Zhang G, Ling J. Application of Metabolomics in Fungal Research. Molecules 2022; 27:7365. [PMID: 36364192 PMCID: PMC9654507 DOI: 10.3390/molecules27217365] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/23/2022] [Accepted: 10/25/2022] [Indexed: 08/27/2023] Open
Abstract
Metabolomics is an essential method to study the dynamic changes of metabolic networks and products using modern analytical techniques, as well as reveal the life phenomena and their inherent laws. Currently, more and more attention has been paid to the development of metabolic histochemistry in the fungus field. This paper reviews the application of metabolomics in fungal research from five aspects: identification, response to stress, metabolite discovery, metabolism engineering, and fungal interactions with plants.
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Affiliation(s)
- Guangyao Li
- School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Tongtong Jian
- Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Xiaojin Liu
- School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Qingtao Lv
- School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Guoying Zhang
- School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
| | - Jianya Ling
- School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao 266237, China
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Alonso-Salces RM, Berrueta LA, Abad-García B, Sasía-Arriba A, Asensio-Regalado C, Dapena E, Gallo B. Untargeted Metabolomic Liquid Chromatography High-Resolution Mass Spectrometry Fingerprinting of Apple Cultivars for the Identification of Biomarkers Related to Resistance to Rosy Apple Aphid. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:13071-13081. [PMID: 35686688 DOI: 10.1021/acs.jafc.2c00738] [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: 06/15/2023]
Abstract
Liquid chromatography high-resolution mass spectrometry fingerprinting together with pattern recognition techniques was used to determine the metabolites involved in the susceptibility of apple cultivars to rosy apple aphid (RAA). Preprocessing of ultra-high-performance liquid chromatography coupled to electrospray ionization and quadrupole time-of-flight mass spectrometry raw data of resistant and susceptible apple cultivars was carried out with XCMS and CAMERA packages. Univariate statistical tools and multivariate data analysis highlighted significant different profiles of the apple metabolomes according to their tolerance to RAA. Optimized and cross-validated Partial least squares discriminant analysis and orthogonal projections to latent structures discriminant analysis models confirmed trans-4-caffeoylquinic acid and 4-p-coumaroylquinic acid as biomarkers for the identification of resistant and susceptible apple cultivars to RAA and disclosed that only hydroxycinnamic acids are involved in the disease susceptibility of cultivars. In this sense, the final steps of the biosynthesis of caffeoylquinic acid (CQA) and p-coumaroylquinic acid (p-CoQA) become decisive because the isomerization of 5-CQA to 4-CQA is favored in resistant cultivars, whereas the isomerization of 5-p-CoQA to 4-p-CoQA is favored in susceptible cultivars.
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Affiliation(s)
- Rosa M Alonso-Salces
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CIAS-IIPROSAM, Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Mar del Plata (UNMdP), Funes 3350, B7602AYL Mar del Plata, Argentina
| | - Luis A Berrueta
- Departamento de Química Analítica, Facultad de Ciencia y Tecnología, Universidad del País Vasco/Euskal Herriko Unibertsitatea (UPV/EHU), Apartado 644, E-48080 Bilbao, Spain
| | - Beatriz Abad-García
- Servicio Central de Análisis, Servicios Generales de Investigación (SGIker), Universidad del País Vasco/Euskal Herriko Unibertsitatea (UPV/EHU), Barrio de Sarriena s/n, E-48940 Leioa, Spain
| | - Andrea Sasía-Arriba
- Departamento de Química Analítica, Facultad de Ciencia y Tecnología, Universidad del País Vasco/Euskal Herriko Unibertsitatea (UPV/EHU), Apartado 644, E-48080 Bilbao, Spain
| | - Carlos Asensio-Regalado
- Departamento de Química Analítica, Facultad de Ciencia y Tecnología, Universidad del País Vasco/Euskal Herriko Unibertsitatea (UPV/EHU), Apartado 644, E-48080 Bilbao, Spain
| | - Enrique Dapena
- Programa de Fruticultura, Servicio Regional de Investigación y Desarrollo Agroalimentario (SERIDA), Carretera de Oviedo s/n, Apartado 13, E-33300 Villaviciosa, Spain
| | - Blanca Gallo
- Departamento de Química Analítica, Facultad de Ciencia y Tecnología, Universidad del País Vasco/Euskal Herriko Unibertsitatea (UPV/EHU), Apartado 644, E-48080 Bilbao, Spain
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Gotsmy M, Brunmair J, Büschl C, Gerner C, Zanghellini J. Probabilistic quotient's work and pharmacokinetics' contribution: countering size effect in metabolic time series measurements. BMC Bioinformatics 2022; 23:379. [PMID: 36114458 PMCID: PMC9482228 DOI: 10.1186/s12859-022-04918-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 09/02/2022] [Indexed: 11/10/2022] Open
Abstract
Metabolomic time course analyses of biofluids are highly relevant for clinical diagnostics. However, many sampling methods suffer from unknown sample sizes, commonly known as size effects. This prevents absolute quantification of biomarkers. Recently, several mathematical post acquisition normalization methods have been developed to overcome these problems either by exploiting already known pharmacokinetic information or by statistical means. Here we present an improved normalization method, MIX, that combines the advantages of both approaches. It couples two normalization terms, one based on a pharmacokinetic model (PKM) and the other representing a popular statistical approach, probabilistic quotient normalization (PQN), in a single model. To test the performance of MIX, we generated synthetic data closely resembling real finger sweat metabolome measurements. We show that MIX normalization successfully tackles key weaknesses of the individual strategies: it (i) reduces the risk of overfitting with PKM, and (ii), contrary to PQN, it allows to compute sample volumes. Finally, we validate MIX by using real finger sweat as well as blood plasma metabolome data and demonstrate that MIX allows to better and more robustly correct for size effects. In conclusion, the MIX method improves the reliability and robustness of quantitative biomarker detection in finger sweat and other biofluids, paving the way for biomarker discovery and hypothesis generation from metabolomic time course data.
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Affiliation(s)
- Mathias Gotsmy
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria
- Vienna Doctoral School in Chemistry, University of Vienna, Vienna, Austria
| | - Julia Brunmair
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria
| | - Christoph Büschl
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria
| | - Christopher Gerner
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria
- Joint Metabolome Facility, University and Medical University of Vienna, Vienna, Austria
| | - Jürgen Zanghellini
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.
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