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Fernandez-Cantos MV, Babu AF, Hanhineva K, Kuipers OP. Identification of metabolites produced by six gut commensal Bacteroidales strains using non-targeted LC-MS/MS metabolite profiling. Microbiol Res 2024; 283:127700. [PMID: 38518452 DOI: 10.1016/j.micres.2024.127700] [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: 12/15/2023] [Revised: 03/05/2024] [Accepted: 03/18/2024] [Indexed: 03/24/2024]
Abstract
As the most abundant gram-negative bacterial order in the gastrointestinal tract, Bacteroidales bacteria have been extensively studied for their contribution to various aspects of gut health. These bacteria are renowned for their involvement in immunomodulation and their remarkable capacity to break down complex carbohydrates and fibers. However, the human gut microbiota is known to produce many metabolites that ultimately mediate important microbe-host and microbe-microbe interactions. To gain further insights into the metabolites produced by the gut commensal strains of this order, we examined the metabolite composition of their bacterial cell cultures in the stationary phase. Based on their abundance in the gastrointestinal tract and their relevance in health and disease, we selected a total of six bacterial strains from the relevant genera Bacteroides, Phocaeicola, Parabacteroides, and Segatella. We grew these strains in modified Gifu anaerobic medium (mGAM) supplemented with mucin, which resembles the gut microbiota's natural environment. Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolite profiling revealed 179 annotated metabolites that had significantly differential abundances between the studied bacterial strains and the control growth medium. Most of them belonged to classes such as amino acids and derivatives, organic acids, and nucleot(s)ides. Of particular interest, Segatella copri DSM 18205 (previously referred to as Prevotella copri) produced substantial quantities of the bioactive metabolites phenylethylamine, tyramine, tryptamine, and ornithine. Parabacteroides merdae CL03T12C32 stood out due to its ability to produce cadaverine, histamine, acetylputrescine, and deoxycarnitine. In addition, we found that strains of the genera Bacteroides, Phocaeicola, and Parabacteroides accumulated considerable amounts of proline-hydroxyproline, a collagen-derived bioactive dipeptide. Collectively, these findings offer a more detailed comprehension of the metabolic potential of these Bacteroidales strains, contributing to a better understanding of their role within the human gut microbiome in health and disease.
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Affiliation(s)
- Maria Victoria Fernandez-Cantos
- Department of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands
| | - Ambrin Farizah Babu
- School of Medicine, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland; Afekta Technologies Ltd., Microkatu 1, Kuopio 70210, Finland
| | - Kati Hanhineva
- School of Medicine, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland; Afekta Technologies Ltd., Microkatu 1, Kuopio 70210, Finland; Department of Life Technologies, Food Sciences Unit, University of Turku, Turku 20014, Finland
| | - Oscar P Kuipers
- Department of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands.
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Lin L, Guo K, Ma H, Zhang J, Lai Z, Zhu W, Mao S. Effects of grain intervention on hypothalamic function and the metabolome of blood and milk in dairy cows. J Anim Sci Biotechnol 2024; 15:71. [PMID: 38822422 PMCID: PMC11143652 DOI: 10.1186/s40104-024-01034-3] [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: 01/02/2024] [Accepted: 04/14/2024] [Indexed: 06/03/2024] Open
Abstract
BACKGROUND The hypothalamus plays a crucial role in the health and productivity of dairy cows, yet studies on its functionality and its impact on peripheral circulation in these animals are relatively scarce, particularly regarding dietary interventions. Therefore, our study undertook a comprehensive analysis, incorporating both metabolomics and transcriptomics, to explore the effects of a grain-based diet on the functionality of the hypothalamus, as well as on blood and milk in dairy cows. RESULTS The hypothalamic metabolome analysis revealed a significant reduction in prostaglandin E2 (PGE2) level as a prominent response to the grain-based diet introduction. Furthermore, the hypothalamic transcriptome profiling showed a notable upregulation in amino acid metabolism due to the grain-based diet. Conversely, the grain-based diet led to the downregulation of genes involved in the metabolic pathway from lecithin to PGE2, including phospholipase A2 (PLA2G4E, PLA2G2A, and PLA2G12B), cyclooxygenase-2 (COX2), and prostaglandin E synthase (PTGES). Additionally, the plasma metabolome analysis indicated a substantial decrease in the level of PGE2, along with a decline in adrenal steroid hormones (tetrahydrocortisol and pregnenolone) following the grain-based diet introduction. Analysis of the milk metabolome showed that the grain-based diet significantly increased uric acid level while notably decreasing PGE2 level. Importantly, PGE2 was identified as a critical metabolic marker in the hypothalamus, blood, and milk in response to grain intervention. Correlation analysis demonstrated a significant correlation among metabolic alterations in the hypothalamus, blood, and milk following the grain-based diet. CONCLUSIONS Our findings suggest a potential link between hypothalamic changes and alterations in peripheral circulation resulting from the introduction of a grain-based diet.
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Affiliation(s)
- Limei Lin
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, National Center for International Research On Animal Gut Nutrition, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
- Ruminant Nutrition and Feed Engineering Technology Research Center, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Kaizhen Guo
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, National Center for International Research On Animal Gut Nutrition, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
- Ruminant Nutrition and Feed Engineering Technology Research Center, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Huiting Ma
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, National Center for International Research On Animal Gut Nutrition, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
- Ruminant Nutrition and Feed Engineering Technology Research Center, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Jiyou Zhang
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, National Center for International Research On Animal Gut Nutrition, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
- Ruminant Nutrition and Feed Engineering Technology Research Center, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Zheng Lai
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, National Center for International Research On Animal Gut Nutrition, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
- Ruminant Nutrition and Feed Engineering Technology Research Center, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Weiyun Zhu
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, National Center for International Research On Animal Gut Nutrition, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
- Ruminant Nutrition and Feed Engineering Technology Research Center, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China
| | - Shengyong Mao
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, National Center for International Research On Animal Gut Nutrition, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China.
- Ruminant Nutrition and Feed Engineering Technology Research Center, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China.
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Huber K, Giralt A, Dreos R, Michenthaler H, Geller S, Barquissau V, Ziegler DV, Tavernari D, Gallart-Ayala H, Krajina K, Jonas K, Ciriello G, Ivanisevic J, Prokesch A, Pichler M, Fajas L. E2F transcription factor-1 modulates expression of glutamine metabolic genes in mouse embryonic fibroblasts and uterine sarcoma cells. BIOCHIMICA ET BIOPHYSICA ACTA. MOLECULAR CELL RESEARCH 2024; 1871:119721. [PMID: 38580088 DOI: 10.1016/j.bbamcr.2024.119721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 03/12/2024] [Accepted: 03/27/2024] [Indexed: 04/07/2024]
Abstract
Metabolic reprogramming is considered as a hallmark of cancer and is clinically exploited as a novel target for therapy. The E2F transcription factor-1 (E2F1) regulates various cellular processes, including proliferative and metabolic pathways, and acts, depending on the cellular and molecular context, as an oncogene or tumor suppressor. The latter is evident by the observation that E2f1-knockout mice develop spontaneous tumors, including uterine sarcomas. This dual role warrants a detailed investigation of how E2F1 loss impacts metabolic pathways related to cancer progression. Our data indicate that E2F1 binds to the promoter of several glutamine metabolism-related genes. Interestingly, the expression of genes in the glutamine metabolic pathway were increased in mouse embryonic fibroblasts (MEFs) lacking E2F1. In addition, we confirm that E2f1-/- MEFs are more efficient in metabolizing glutamine and producing glutamine-derived precursors for proliferation. Mechanistically, we observe a co-occupancy of E2F1 and MYC on glutamine metabolic promoters, increased MYC binding after E2F1 depletion and that silencing of MYC decreased the expression of glutamine-related genes in E2f1-/- MEFs. Analyses of transcriptomic profiles in 29 different human cancers identified uterine sarcoma that showed a negative correlation between E2F1 and glutamine metabolic genes. CRISPR/Cas9 knockout of E2F1 in the uterine sarcoma cell line SK-UT-1 confirmed elevated glutamine metabolic gene expression, increased proliferation and increased MYC binding to glutamine-related promoters upon E2F1 loss. Together, our data suggest a crucial role of E2F1 in energy metabolism and metabolic adaptation in uterine sarcoma cells.
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Affiliation(s)
- Katharina Huber
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland; Division of Oncology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Albert Giralt
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - René Dreos
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Helene Michenthaler
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Division of Cell Biology, Histology and Embryology, Medical University of Graz, Graz, Austria
| | - Sarah Geller
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Valentin Barquissau
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Dorian V Ziegler
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Daniele Tavernari
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Léman, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Hector Gallart-Ayala
- Metabolomics Unit, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Katarina Krajina
- Division of Oncology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Katharina Jonas
- Division of Oncology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Giovanni Ciriello
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Léman, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Julijana Ivanisevic
- Metabolomics Unit, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Andreas Prokesch
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Division of Cell Biology, Histology and Embryology, Medical University of Graz, Graz, Austria; BioTechMed-Graz, Graz, Austria
| | - Martin Pichler
- Division of Oncology, Department of Internal Medicine, Medical University of Graz, Graz, Austria; Translational Oncology, II. Med. Clinics, University Hospital of Augsburg, Augsburg, Germany
| | - Lluis Fajas
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
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Naznin M, Alam R, Alam MB, Jung MJ, Lee SH, Kim S. Biological activities, identification, method development, and validation for analysis of polyphenolic compounds in Nymphaea rubra flowers and leaves by UHPLC-Q-cIM-TOF-MS and UHPLC-TQ-MS. PHYTOCHEMICAL ANALYSIS : PCA 2024; 35:799-816. [PMID: 38297293 DOI: 10.1002/pca.3329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 01/08/2024] [Accepted: 01/09/2024] [Indexed: 02/02/2024]
Abstract
INTRODUCTION Nymphaea rubra belongs to the Nymphaea family and is regarded as a vegetable used in traditional medicine to cure several ailments. These species are rich in phenolic acid, flavonoids, and hydrolysable tannin. OBJECTIVE This study aimed to assess the biological activities of Nymphaea rubra flowers (NRF) and leaves (NRL) by identifying and quantifying their polyphenolic compounds using ultra-performance liquid chromatography coupled to quadrupole cyclic ion mobility time-of-flight mass spectrometry (UHPLC-Q-cIM-TOF-MS) and triple quadrupole mass spectrometry (UHPLC-TQ-MS). METHODOLOGY NRF and NRL powder was extracted with methanol and fractionated using hexane, ethylacetate, and water. Antioxidant and α-glucosidase, and tyrosinase enzyme inhibitory activities were evaluated. The polyphenolic components of NRF and NRL were identified and quantified using UHPLC-Q-cIM-TOF-MS and UHPLC-TQ-MS. The method was validated using linearity, precision, accuracy, limit of detection (LOD), and lower limit of quantification (LLOQ). RESULTS Bioactive substances and antioxidants were highest in the ethylacetate fraction of flowers and leaves. Principal component analysis showed how solvent and plant components affect N. rubra's bioactivity and bioactive compound extraction. A total of 67 compounds were identified, and among them 21 significant polyphenols were quantified. Each calibration curve had R2 > 0.998. The LOD and LLOQ varied from 0.007 to 0.09 μg/mL and from 0.01 to 0.1 μg/mL, respectively. NRF contained a significant amount of gallic acid (10.1 mg/g), while NRL contained abundant pentagalloylglucose (2.8 mg/g). CONCLUSION The developed method is simple, rapid, and selective for the identification and quantification of bioactive molecules. These findings provide a scientific basis for N. rubra's well-documented biological effects.
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Affiliation(s)
- Marufa Naznin
- Department of Chemistry, Kyungpook National University, Daegu, South Korea
| | - Rafiqul Alam
- Department of Chemistry, Kyungpook National University, Daegu, South Korea
| | - Md Badrul Alam
- Department of Food Science and Biotechnology, Graduate School, Kyungpook National University, Daegu, South Korea
- Food and Bio-Industry Research Institute, Inner Beauty/Antiaging Center, Kyungpook National University, Daegu, South Korea
| | - Maeng-Joon Jung
- Department of Chemistry, Kyungpook National University, Daegu, South Korea
| | - Sang-Han Lee
- Department of Food Science and Biotechnology, Graduate School, Kyungpook National University, Daegu, South Korea
- Food and Bio-Industry Research Institute, Inner Beauty/Antiaging Center, Kyungpook National University, Daegu, South Korea
| | - Sunghwan Kim
- Department of Chemistry, Kyungpook National University, Daegu, South Korea
- Mass Spectrometry Converging Research Center and Green-Nano Materials Research Center, Daegu, South Korea
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5
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Aggerbeck MR, Frøkjær EE, Johansen A, Ellegaard-Jensen L, Hansen LH, Hansen M. Non-target analysis of Danish wastewater treatment plant effluent: Statistical analysis of chemical fingerprinting as a step toward a future monitoring tool. ENVIRONMENTAL RESEARCH 2024; 257:119242. [PMID: 38821457 DOI: 10.1016/j.envres.2024.119242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 04/25/2024] [Accepted: 05/26/2024] [Indexed: 06/02/2024]
Abstract
In an attempt to discover and characterize the plethora of xenobiotic substances, this study investigates chemical compounds released into the environment with wastewater effluents. A novel non-targeted screening methodology based on ultra-high resolution Orbitrap mass spectrometry and nanoflow ultra-high performance liquid chromatography together with a newly optimized data-processing pipeline were applied to effluent samples from two state-of-the-art and one small wastewater treatment facility. In total, 785 molecular structures were obtained, of which 38 were identified as single compounds, while 480 structures were identified at a putative level. Most of these substances were therapeutics and drugs, present as parent compounds and metabolites. Using R packages Phyloseq and MetacodeR, originally developed for bioinformatics, significant differences in xenobiotic presence in the wastewater effluents between the three sites were demonstrated.
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Affiliation(s)
- Marie Rønne Aggerbeck
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark; Aarhus University Centre for Water Technology (WATEC), Aarhus University, Vejlsøvej 25, 8600, Silkeborg, Denmark.
| | - Emil Egede Frøkjær
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark
| | - Anders Johansen
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark; Aarhus University Centre for Water Technology (WATEC), Aarhus University, Vejlsøvej 25, 8600, Silkeborg, Denmark; Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg, Denmark; Aarhus University Centre for Circular Bioeconomy, Aarhus University, 8830 Tjele, Denmark
| | - Lea Ellegaard-Jensen
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark; Aarhus University Centre for Water Technology (WATEC), Aarhus University, Vejlsøvej 25, 8600, Silkeborg, Denmark
| | - Lars Hestbjerg Hansen
- Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg, Denmark
| | - Martin Hansen
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000, Roskilde, Denmark; Aarhus University Centre for Water Technology (WATEC), Aarhus University, Vejlsøvej 25, 8600, Silkeborg, Denmark.
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6
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Baker ES, Uritboonthai W, Aisporna A, Hoang C, Heyman HM, Connell L, Olivier-Jimenez D, Giera M, Siuzdak G. METLIN-CCS Lipid Database: An authentic standards resource for lipid classification and identification. Nat Metab 2024:10.1038/s42255-024-01058-z. [PMID: 38802544 DOI: 10.1038/s42255-024-01058-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Affiliation(s)
- Erin S Baker
- Department of Chemistry, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | | | - Aries Aisporna
- Scripps Center of Metabolomics and Mass Spectrometry, La Jolla, CA, USA
| | - Corey Hoang
- Scripps Center of Metabolomics and Mass Spectrometry, La Jolla, CA, USA
| | - Heino M Heyman
- Bruker Daltonics, Bruker Scientific LLC, Billerica, MA, USA
- Metabolon Inc., 617 Davis Drive. Suite 100, Morrisville, NC, USA
| | - Lisa Connell
- Avanti Polar Lipids (part of Croda International), Alabaster, AL, USA
| | - Damien Olivier-Jimenez
- Leiden University Medical Center, Center for Proteomics and Metabolomics, Leiden, The Netherlands
- The Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden, The Netherlands
| | - Martin Giera
- Leiden University Medical Center, Center for Proteomics and Metabolomics, Leiden, The Netherlands
- The Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden, The Netherlands
| | - Gary Siuzdak
- Scripps Center of Metabolomics and Mass Spectrometry, La Jolla, CA, USA.
- Department of Chemistry, Molecular and Computational Biology Scripps Research Institute, La Jolla, CA, USA.
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7
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Loveday EK, Welhaven H, Erdogan AE, Hain K, Chang CB, June RK, Taylor MP. Starve a cold or feed a fever? Identifying cellular metabolic changes following infection and exposure to SARS-CoV-2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.22.595410. [PMID: 38826440 PMCID: PMC11142155 DOI: 10.1101/2024.05.22.595410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Viral infections induce major shifts in cellular metabolism elicited by active viral replication and antiviral responses. For the virus, harnessing cellular metabolism and evading changes that limit replication are essential for productive viral replication. In contrast, the cellular response to infection disrupts metabolic pathways to prevent viral replication and promote an antiviral state in the host cell and neighboring bystander cells. This competition between the virus and cell results in measurable shifts in cellular metabolism that differ depending on the virus, cell type, and extracellular environment. The resulting metabolic shifts can be observed and analyzed using global metabolic profiling techniques to identify pathways that are critical for either viral replication or cellular defense. SARS-CoV-2 is a respiratory virus that can exhibit broad tissue tropism and diverse, yet inconsistent, symptomatology. While the factors that determine the presentation and severity of SARS-CoV-2 infection remain unclear, metabolic syndromes are associated with more severe manifestations of SARS-CoV-2 disease. Despite these observations a critical knowledge gap remains between cellular metabolic responses and SARS-CoV-2 infection. Using a well-established untargeted metabolomics analysis workflow, we compared SARS-CoV-2 infection of human lung carcinoma cells. We identified significant changes in metabolic pathways that correlate with either productive or non-productive viral infection. This information is critical for characterizing the factors that contribute to SARS-CoV-2 replication that could be targeted for therapeutic interventions to limit viral disease.
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Affiliation(s)
- Emma Kate Loveday
- Center for Biofilm Engineering, Montana State University, Bozeman MT 59717
- Department of Chemical and Biological Engineering, Montana State University, Bozeman MT 59717
| | - Hope Welhaven
- Chemistry and Biochemistry, Montana State University, Bozeman MT 59717
| | - Ayten Ebru Erdogan
- Department of Chemical and Biological Engineering, Montana State University, Bozeman MT 59717
| | - Kyle Hain
- Microbiology and Cell Biology, Montana State University, Bozeman MT 59717
| | - Connie B. Chang
- Center for Biofilm Engineering, Montana State University, Bozeman MT 59717
- Department of Chemical and Biological Engineering, Montana State University, Bozeman MT 59717
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905
| | - Ronald K. June
- Department of Mechanical & Industrial Engineering, Montana State University, Bozeman MT 59717
| | - Matthew P. Taylor
- Microbiology and Cell Biology, Montana State University, Bozeman MT 59717
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8
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Han S, Guiberson ER, Li Y, Sonnenburg JL. High-throughput identification of gut microbiome-dependent metabolites. Nat Protoc 2024:10.1038/s41596-024-00980-6. [PMID: 38740909 DOI: 10.1038/s41596-024-00980-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 01/18/2024] [Indexed: 05/16/2024]
Abstract
A significant hurdle that has limited progress in microbiome science has been identifying and studying the diverse set of metabolites produced by gut microbes. Gut microbial metabolism produces thousands of difficult-to-identify metabolites, which present a challenge to study their roles in host biology. In recent years, mass spectrometry-based metabolomics has become one of the core technologies for identifying small metabolites. However, metabolomics expertise, ranging from sample preparation to instrument use and data analysis, is often lacking in academic labs. Most targeted metabolomics methods provide high levels of sensitivity and quantification, while they are limited to a panel of predefined molecules that may not be informative to microbiome-focused studies. Here we have developed a gut microbe-focused and wide-spectrum metabolomic protocol using liquid chromatography-mass spectrometry and bioinformatic analysis. This protocol enables users to carry out experiments from sample collection to data analysis, only requiring access to a liquid chromatography-mass spectrometry instrument, which is often available at local core facilities. By applying this protocol to samples containing human gut microbial metabolites, spanning from culture supernatant to human biospecimens, our approach enables high-confidence identification of >800 metabolites that can serve as candidate mediators of microbe-host interactions. We expect this protocol will lower the barrier to tracking gut bacterial metabolism in vitro and in mammalian hosts, propelling hypothesis-driven mechanistic studies and accelerating our understanding of the gut microbiome at the chemical level.
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Affiliation(s)
- Shuo Han
- Department of Biochemistry, Duke University School of Medicine, Durham, NC, USA.
- Duke Microbiome Center, Duke University School of Medicine, Durham, NC, USA.
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA.
| | - Emma R Guiberson
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA
| | - Yuxin Li
- Biochemistry Graduate Program, Duke University School of Medicine, Durham, NC, USA
| | - Justin L Sonnenburg
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA.
- Chan-Zuckerberg Biohub, San Francisco, CA, USA.
- Center for Human Microbiome Studies, Stanford, CA, USA.
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9
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Pang Z, Xu L, Viau C, Lu Y, Salavati R, Basu N, Xia J. MetaboAnalystR 4.0: a unified LC-MS workflow for global metabolomics. Nat Commun 2024; 15:3675. [PMID: 38693118 PMCID: PMC11063062 DOI: 10.1038/s41467-024-48009-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 04/18/2024] [Indexed: 05/03/2024] Open
Abstract
The wide applications of liquid chromatography - mass spectrometry (LC-MS) in untargeted metabolomics demand an easy-to-use, comprehensive computational workflow to support efficient and reproducible data analysis. However, current tools were primarily developed to perform specific tasks in LC-MS based metabolomics data analysis. Here we introduce MetaboAnalystR 4.0 as a streamlined pipeline covering raw spectra processing, compound identification, statistical analysis, and functional interpretation. The key features of MetaboAnalystR 4.0 includes an auto-optimized feature detection and quantification algorithm for LC-MS1 spectra processing, efficient MS2 spectra deconvolution and compound identification for data-dependent or data-independent acquisition, and more accurate functional interpretation through integrated spectral annotation. Comprehensive validation studies using LC-MS1 and MS2 spectra obtained from standards mixtures, dilution series and clinical metabolomics samples have shown its excellent performance across a wide range of common tasks such as peak picking, spectral deconvolution, and compound identification with good computing efficiency. Together with its existing statistical analysis utilities, MetaboAnalystR 4.0 represents a significant step toward a unified, end-to-end workflow for LC-MS based global metabolomics in the open-source R environment.
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Affiliation(s)
- Zhiqiang Pang
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Lei Xu
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Charles Viau
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Yao Lu
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
| | - Reza Salavati
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Jianguo Xia
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada.
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada.
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10
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Xu Y, Cao L, Chen Y, Zhang Z, Liu W, Li H, Ding C, Pu J, Qian K, Xu W. Integrating Machine Learning in Metabolomics: A Path to Enhanced Diagnostics and Data Interpretation. SMALL METHODS 2024:e2400305. [PMID: 38682615 DOI: 10.1002/smtd.202400305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Revised: 04/07/2024] [Indexed: 05/01/2024]
Abstract
Metabolomics, leveraging techniques like NMR and MS, is crucial for understanding biochemical processes in pathophysiological states. This field, however, faces challenges in metabolite sensitivity, data complexity, and omics data integration. Recent machine learning advancements have enhanced data analysis and disease classification in metabolomics. This study explores machine learning integration with metabolomics to improve metabolite identification, data efficiency, and diagnostic methods. Using deep learning and traditional machine learning, it presents advancements in metabolic data analysis, including novel algorithms for accurate peak identification, robust disease classification from metabolic profiles, and improved metabolite annotation. It also highlights multiomics integration, demonstrating machine learning's potential in elucidating biological phenomena and advancing disease diagnostics. This work contributes significantly to metabolomics by merging it with machine learning, offering innovative solutions to analytical challenges and setting new standards for omics data analysis.
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Affiliation(s)
- Yudian Xu
- Department of Traditional Chinese Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China
| | - Linlin Cao
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Yifan Chen
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Ziyue Zhang
- School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Wanshan Liu
- School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - He Li
- Department of Traditional Chinese Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China
| | - Chenhuan Ding
- Department of Traditional Chinese Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China
| | - Jun Pu
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Kun Qian
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai, 200127, P. R. China
- School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Wei Xu
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai, 200127, P. R. China
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11
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Zhao X, Ge W, Miao Z. Integrative metabolomic and transcriptomic analyses reveals the accumulation patterns of key metabolites associated with flavonoids and terpenoids of Gynostemma pentaphyllum (Thunb.) Makino. Sci Rep 2024; 14:8644. [PMID: 38622163 PMCID: PMC11018608 DOI: 10.1038/s41598-024-57716-5] [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: 01/16/2024] [Accepted: 03/21/2024] [Indexed: 04/17/2024] Open
Abstract
Gynostemma pentaphyllum (Thunb.) Makino (G. pentaphyllum) is a medicinal and edible plant with multiple functions of liver protection, anti-tumor, anti-inflammation, balancing blood sugar and blood lipids. The nutritional value of the G. pentaphyllum plant is mainly due to its rich variety of biologically active substances, such as flavonoids, terpenes and polysaccharides. In this study, we performed a comprehensive analysis combining metabolomics and root, stem and leaf transcriptomic data of G. pentaphyllum. We used transcriptomics and metabolomics data to construct a dynamic regulatory network diagram of G. pentaphyllum flavonoids and terpenoids, and screened the transcription factors involved in flavonoids and terpenoids, including basic helix-loop-helix (bHLH), myb-related, WRKY, AP2/ERF. Transcriptome analysis results showed that among the DEGs related to the synthesis of flavonoids and terpenoids, dihydroflavonol 4-reductase (DFR) and geranylgeranyl diphosphate synthases (GGPPS) were core genes. This study presents a dynamic image of gene expression in different tissues of G. pentaphyllum, elucidating the key genes and metabolites of flavonoids and terpenoids. This study is beneficial to a deeper understanding of the medicinal plants of G. pentaphyllum, and also provides a scientific basis for further regulatory mechanisms of plant natural product synthesis pathways and drug development.
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Affiliation(s)
- Xiaomeng Zhao
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300350, People's Republic of China
| | - Weiwei Ge
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300350, People's Republic of China
| | - Zhi Miao
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300350, People's Republic of China.
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12
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de Souza WM, Fumagalli MJ, de Lima STS, Parise PL, Carvalho DCM, Hernandez C, de Jesus R, Delafiori J, Candido DS, Carregari VC, Muraro SP, Souza GF, Simões Mello LM, Claro IM, Díaz Y, Kato RB, Trentin LN, Costa CHS, Maximo ACBM, Cavalcante KF, Fiuza TS, Viana VAF, Melo MEL, Ferraz CPM, Silva DB, Duarte LMF, Barbosa PP, Amorim MR, Judice CC, Toledo-Teixeira DA, Ramundo MS, Aguilar PV, Araújo ELL, Costa FTM, Cerqueira-Silva T, Khouri R, Boaventura VS, Figueiredo LTM, Fang R, Moreno B, López-Vergès S, Mello LP, Skaf MS, Catharino RR, Granja F, Martins-de-Souza D, Plante JA, Plante KS, Sabino EC, Diamond MS, Eugenin E, Proença-Módena JL, Faria NR, Weaver SC. Pathophysiology of chikungunya virus infection associated with fatal outcomes. Cell Host Microbe 2024; 32:606-622.e8. [PMID: 38479396 PMCID: PMC11018361 DOI: 10.1016/j.chom.2024.02.011] [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: 08/16/2023] [Revised: 12/08/2023] [Accepted: 02/16/2024] [Indexed: 03/28/2024]
Abstract
Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that causes acute, subacute, and chronic human arthritogenic diseases and, in rare instances, can lead to neurological complications and death. Here, we combined epidemiological, virological, histopathological, cytokine, molecular dynamics, metabolomic, proteomic, and genomic analyses to investigate viral and host factors that contribute to chikungunya-associated (CHIK) death. Our results indicate that CHIK deaths are associated with multi-organ infection, central nervous system damage, and elevated serum levels of pro-inflammatory cytokines and chemokines compared with survivors. The histopathologic, metabolite, and proteomic signatures of CHIK deaths reveal hemodynamic disorders and dysregulated immune responses. The CHIKV East-Central-South-African lineage infecting our study population causes both fatal and survival cases. Additionally, CHIKV infection impairs the integrity of the blood-brain barrier, as evidenced by an increase in permeability and altered tight junction protein expression. Overall, our findings improve the understanding of CHIK pathophysiology and the causes of fatal infections.
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Affiliation(s)
- William M de Souza
- Department of Microbiology, Immunology and Molecular Genetics, University of Kentucky, College of Medicine, Lexington, KY, USA; Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA; World Reference Center for Emerging Viruses and Arboviruses, University of Texas Medical Branch, Galveston, TX, USA; Global Virus Network, Baltimore, MD, USA.
| | - Marcilio J Fumagalli
- Laboratory of Molecular Immunology, The Rockefeller University, New York, NY, USA
| | - Shirlene T S de Lima
- Laboratório Central de Saúde Pública do Ceará, Fortaleza, Ceará, Brazil; Laboratory of Emerging Viruses, Department of Genetics, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | - Pierina L Parise
- Laboratory of Emerging Viruses, Department of Genetics, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil; Department of Pathology, University of Texas Medical Branch, Galveston, TX, USA
| | - Deyse C M Carvalho
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA; Laboratory of Immunobiotechnology, Biotechnology Center, Federal University of Paraíba, João Pessoa, Paraíba, Brazil
| | - Cristian Hernandez
- Department of Neurobiology, University of Texas Medical Branch, Galveston, TX, USA
| | - Ronaldo de Jesus
- Coordenação Geral dos Laboratórios de Saúde Pública, Secretaria de Vigilância em Saúde, Ministério da Saúde, Brasília, Brazil; Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Jeany Delafiori
- Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - Darlan S Candido
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK; Department of Zoology, University of Oxford, Oxford, UK; Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Victor C Carregari
- Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | - Stefanie P Muraro
- Laboratory of Emerging Viruses, Department of Genetics, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | - Gabriela F Souza
- Laboratory of Emerging Viruses, Department of Genetics, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | | | - Ingra M Claro
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK; Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Yamilka Díaz
- Department of Research in Virology and Biotechnology, Gorgas Memorial Institute of Health Studies, Panama, Panama
| | - Rodrigo B Kato
- Coordenação Geral dos Laboratórios de Saúde Pública, Secretaria de Vigilância em Saúde, Ministério da Saúde, Brasília, Brazil; Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Lucas N Trentin
- Institute of Chemistry and Center for Computing in Engineering and Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - Clauber H S Costa
- Institute of Chemistry and Center for Computing in Engineering and Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | | | | | - Tayna S Fiuza
- Laboratório Central de Saúde Pública do Ceará, Fortaleza, Ceará, Brazil; Programa de Pós Graduação em Bioinformática, Instituto Metrópole Digital, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Vânia A F Viana
- Laboratório Central de Saúde Pública do Ceará, Fortaleza, Ceará, Brazil
| | | | | | - Débora B Silva
- Laboratório Central de Saúde Pública do Ceará, Fortaleza, Ceará, Brazil
| | | | - Priscilla P Barbosa
- Laboratory of Emerging Viruses, Department of Genetics, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | - Mariene R Amorim
- Laboratory of Emerging Viruses, Department of Genetics, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | - Carla C Judice
- Laboratory of Tropical Diseases, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | - Daniel A Toledo-Teixeira
- Laboratory of Emerging Viruses, Department of Genetics, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | - Mariana S Ramundo
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Patricia V Aguilar
- Department of Pathology, University of Texas Medical Branch, Galveston, TX, USA; Center for Tropical Diseases, Institute for Human Infection and Immunity, University of Texas Medical Branch, Galveston, TX, USA
| | - Emerson L L Araújo
- Coordenação Geral de Atenção às Doenças Transmissíveis na Atenção Primária, Departamento de Gestão ao cuidado Integral, Secretaria de Atenção Primária à Saúde, Ministério da Saúde, Brasília, Brazil
| | - Fabio T M Costa
- Laboratory of Tropical Diseases, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | - Thiago Cerqueira-Silva
- Universidade Federal da Bahia, Faculdade de Medicina, Salvador, Bahia, Brazil; Fundação Oswaldo Cruz, Instituto Gonçalo Muniz, Laboratório de Medicina e Saúde Pública de Precisão, Salvador, Bahia, Brazil
| | - Ricardo Khouri
- Universidade Federal da Bahia, Faculdade de Medicina, Salvador, Bahia, Brazil; Fundação Oswaldo Cruz, Instituto Gonçalo Muniz, Laboratório de Medicina e Saúde Pública de Precisão, Salvador, Bahia, Brazil
| | - Viviane S Boaventura
- Universidade Federal da Bahia, Faculdade de Medicina, Salvador, Bahia, Brazil; Fundação Oswaldo Cruz, Instituto Gonçalo Muniz, Laboratório de Medicina e Saúde Pública de Precisão, Salvador, Bahia, Brazil; Hospital Santa Izabel, Santa Casa de Misericórdia da Bahia, Serviço de Otorrinolaringologia, Salvador, Bahia, Brazil
| | - Luiz Tadeu M Figueiredo
- Virology Research Centre, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
| | - Rong Fang
- Department of Pathology, University of Texas Medical Branch, Galveston, TX, USA
| | - Brechla Moreno
- Department of Research in Virology and Biotechnology, Gorgas Memorial Institute of Health Studies, Panama, Panama
| | - Sandra López-Vergès
- Department of Research in Virology and Biotechnology, Gorgas Memorial Institute of Health Studies, Panama, Panama; Sistema Nacional de Investigación from SENACYT, Panama, Panama
| | | | - Munir S Skaf
- Institute of Chemistry and Center for Computing in Engineering and Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - Rodrigo R Catharino
- Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - Fabiana Granja
- Laboratory of Emerging Viruses, Department of Genetics, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil; Biodiversity Research Centre, Federal University of Roraima, Boa Vista, Roraima, Brazil
| | - Daniel Martins-de-Souza
- Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil; D'Or Institute for Research and Education, São Paulo, São Paulo, Brazil; Experimental Medicine Research Cluster, University of Campinas, Campinas, São Paulo, Brazil
| | - Jessica A Plante
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA; World Reference Center for Emerging Viruses and Arboviruses, University of Texas Medical Branch, Galveston, TX, USA
| | - Kenneth S Plante
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA; World Reference Center for Emerging Viruses and Arboviruses, University of Texas Medical Branch, Galveston, TX, USA
| | - Ester C Sabino
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Michael S Diamond
- Departments of Medicine, Molecular Microbiology, Pathology & Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Eliseo Eugenin
- Department of Neurobiology, University of Texas Medical Branch, Galveston, TX, USA
| | - José Luiz Proença-Módena
- Laboratory of Emerging Viruses, Department of Genetics, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | - Nuno R Faria
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK; Department of Zoology, University of Oxford, Oxford, UK; Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Scott C Weaver
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA; World Reference Center for Emerging Viruses and Arboviruses, University of Texas Medical Branch, Galveston, TX, USA; Global Virus Network, Baltimore, MD, USA; Institute for Human Infection and Immunity, University of Texas Medical Branch, Galveston, TX, USA
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13
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Hoang C, Uritboonthai W, Hoang L, Billings EM, Aisporna A, Nia FA, Derks RJE, Williamson JR, Giera M, Siuzdak G. Tandem Mass Spectrometry across Platforms. Anal Chem 2024; 96:5478-5488. [PMID: 38529642 PMCID: PMC11007677 DOI: 10.1021/acs.analchem.3c05576] [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: 12/07/2023] [Revised: 02/12/2024] [Accepted: 03/18/2024] [Indexed: 03/27/2024]
Abstract
PubChem serves as a comprehensive repository, housing over 100 million unique chemical structures representing the breadth of our chemical knowledge across numerous fields including metabolism, pharmaceuticals, toxicology, cosmetics, agriculture, and many more. Rapid identification of these small molecules increasingly relies on electrospray ionization (ESI) paired with tandem mass spectrometry (MS/MS), particularly by comparison to genuine standard MS/MS data sets. Despite its widespread application, achieving consistency in MS/MS data across various analytical platforms remains an unaddressed concern. This study evaluated MS/MS data derived from one hundred molecular standards utilizing instruments from five manufacturers, inclusive of quadrupole time-of-flight (QTOF) and quadrupole orbitrap "exactive" (QE) mass spectrometers by Agilent (QTOF), Bruker (QTOF), SCIEX (QTOF), Waters (QTOF), and Thermo QE. We assessed fragment ion variations at multiple collisional energies (0, 10, 20, and 40 eV) using the cosine scoring algorithm for comparisons and the number of fragments observed. A parallel visual analysis of the MS/MS spectra across instruments was conducted, consistent with a standard procedure that is used to circumvent the still prevalent issue of mischaracterizations as shown for dimethyl sphingosine and C20 sphingosine. Our analysis revealed a notable consistency in MS/MS data and identifications, with fragment ions' m/z values exhibiting the highest concordance between instrument platforms at 20 eV, the other collisional energies (0, 10, and 40 eV) were significantly lower. While moving toward a standardized ESI MS/MS protocol is required for dependable molecular characterization, our results also underscore the continued importance of corroborating MS/MS data against standards to ensure accurate identifications. Our findings suggest that ESI MS/MS manufacturers, akin to the established norms for gas chromatography mass spectrometry instruments, should standardize the collision energy at 20 eV across different instrument platforms.
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Affiliation(s)
- Corey Hoang
- Scripps
Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Winnie Uritboonthai
- Scripps
Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Linh Hoang
- Scripps
Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Elizabeth M. Billings
- Scripps
Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Aries Aisporna
- Scripps
Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Farshad A. Nia
- Department
of Integrative Structural and Computational Biology, Department of
Chemistry, The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Rico J. E. Derks
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Albinusdreef 2, Leiden 2333ZA, Netherlands
| | - James R. Williamson
- Department
of Integrative Structural and Computational Biology, Department of
Chemistry, The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Martin Giera
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Albinusdreef 2, Leiden 2333ZA, Netherlands
- The
Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden 2333ZA, The Netherlands
| | - Gary Siuzdak
- Scripps
Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
- Departments
of Chemistry, Molecular, and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
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14
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Dedon LR, Yuan H, Chi J, Gu H, Arias AJ, Covault JM, Zhou Y. Baseline gut microbiome and metabolites are correlated with alcohol consumption in a zonisamide clinical trial of heavy drinking alcoholic civilians. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.02.24305199. [PMID: 38633809 PMCID: PMC11023652 DOI: 10.1101/2024.04.02.24305199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Development and severity of alcohol use disorder (AUD) has been linked to variations in gut microbiota and their associated metabolites in both animal and human studies. However, the involvement of the gut microbiome in alcohol consumption of individuals with AUD undergoing treatment remains unclear. To address this, stool samples (n=48) were collected at screening (baseline) and trial completion from a single site of a multi-site double-blind, placebo-controlled trial of Zonisamide in individuals with AUD. Alcohol consumption, gamma-glutamyl transferase (GGT), and phosphatidylethanol (PEth)levels were measured both at baseline and endpoint of 16-week trial period. Fecal microbiome was analyzed via 16S rRNA sequencing and metabolome via untargeted LC-MS. Both sex (p = 0.003) and psychotropic medication usage (p = 0.025) are associated with baseline microbiome composition. The relative abundance of 12 genera at baseline was correlated with percent drinking reduction, baseline and endpoint alcohol consumption, and changes in GGT and PeTH over the course of treatment (p.adj < 0.05). Overall microbiome community structure at baseline differed between high and low responders (67-100% and 0-33% drinking reduction, respectively; p = 0.03). A positive relationship between baseline fecal GABA levels and percent drinking reduction (R=0.43, p < 0.05) was identified by microbiome function prediction and confirmed by ELISA and metabolomics. Predicted microbiome function and metabolomics analysis have found that tryptophan metabolic pathways are over-represented in low responders. These findings highlight importance of baseline microbiome and metabolites in alcohol consumption in AUD patients undergoing zonisamide treatment.
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15
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Lu P, Li L. MGDHGS: Gene-bridged metabolite-disease relationships prediction via GraphSAGE and self-attention mechanism. Comput Biol Chem 2024; 109:108036. [PMID: 38422603 DOI: 10.1016/j.compbiolchem.2024.108036] [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: 11/07/2023] [Revised: 02/14/2024] [Accepted: 02/21/2024] [Indexed: 03/02/2024]
Abstract
Metabolites represent the underlying information of biological systems. Revealing the links between metabolites and diseases can facilitate the development of targeted drugs. Traditional biological experiments can be used to validate the relationships of metabolite-disease, but these methods are time-consuming and labor-intensive. In contrast, the prevailing computational methods have improved efficiency but primarily rely on the metabolite-disease interactions, overlooking the impact of other biological components. To remedy the problem, we present a novel computational framework (MGDHGS) based on metabolite-gene-disease heterogeneous network to forecast potential associations. Specifically, we initially integrate data from multiple sources to construct metabolite-gene-disease heterogeneous network that includes known associations and computationally-derived similarities. Then, the GraphSAGE is harnessed to learn the low dimensional neighborhood representation in the heterogeneous network and self-attention mechanism is applied to effectively capture the connectivity patterns, which contributions to combine with nodes intrinsic and extrinsic features. Finally, the ultimate relationships probability scores are predicted by linear regression based on the these characteristics. The five-fold cross-validation showcases impressive AUC (0.9734) and PR (0.9718) for MGDHGS compared with five state-of-the-art methods, and the case studies validate that the metabolite-disease associations predicted by MGDHGS can be substantiated through pertinent biological experiments. The findings of this study show great potential contribution in the development of targeted drugs as well as offering solid support for our understanding of the complex interactions between metabolites, genes and diseases.
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Affiliation(s)
- Pengli Lu
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, Gansu, PR China.
| | - Ling Li
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, Gansu, PR China.
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16
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Bhosle A, Bae S, Zhang Y, Chun E, Avila-Pacheco J, Geistlinger L, Pishchany G, Glickman JN, Michaud M, Waldron L, Clish CB, Xavier RJ, Vlamakis H, Franzosa EA, Garrett WS, Huttenhower C. Integrated annotation prioritizes metabolites with bioactivity in inflammatory bowel disease. Mol Syst Biol 2024; 20:338-361. [PMID: 38467837 PMCID: PMC10987656 DOI: 10.1038/s44320-024-00027-8] [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: 09/20/2023] [Revised: 02/13/2024] [Accepted: 02/15/2024] [Indexed: 03/13/2024] Open
Abstract
Microbial biochemistry is central to the pathophysiology of inflammatory bowel diseases (IBD). Improved knowledge of microbial metabolites and their immunomodulatory roles is thus necessary for diagnosis and management. Here, we systematically analyzed the chemical, ecological, and epidemiological properties of ~82k metabolic features in 546 Integrative Human Microbiome Project (iHMP/HMP2) metabolomes, using a newly developed methodology for bioactive compound prioritization from microbial communities. This suggested >1000 metabolic features as potentially bioactive in IBD and associated ~43% of prevalent, unannotated features with at least one well-characterized metabolite, thereby providing initial information for further characterization of a significant portion of the fecal metabolome. Prioritized features included known IBD-linked chemical families such as bile acids and short-chain fatty acids, and less-explored bilirubin, polyamine, and vitamin derivatives, and other microbial products. One of these, nicotinamide riboside, reduced colitis scores in DSS-treated mice. The method, MACARRoN, is generalizable with the potential to improve microbial community characterization and provide therapeutic candidates.
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Affiliation(s)
- Amrisha Bhosle
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Harvard Chan Microbiome in Public Health Center, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Sena Bae
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Yancong Zhang
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Harvard Chan Microbiome in Public Health Center, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Eunyoung Chun
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | | | - Ludwig Geistlinger
- Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA
- Center for Computational Biomedicine, Harvard Medical School, Boston, MA, USA
| | - Gleb Pishchany
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jonathan N Glickman
- Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Pathology, Harvard Medical School, Boston, MA, USA
| | - Monia Michaud
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Levi Waldron
- Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA
| | - Clary B Clish
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ramnik J Xavier
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hera Vlamakis
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eric A Franzosa
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Harvard Chan Microbiome in Public Health Center, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Wendy S Garrett
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Chan Microbiome in Public Health Center, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Curtis Huttenhower
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
- Harvard Chan Microbiome in Public Health Center, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
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17
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Zhang K, Li H, Shi J, Liu W, Wang Y, Tu P, Li J, Song Y. Strategy strengthens structural identification through hyphenating full collision energy ramp-MS 2 and full exciting energy ramp-MS 3 spectra: An application for metabolites identification of rosmarinic acid. Anal Chim Acta 2024; 1296:342346. [PMID: 38401935 DOI: 10.1016/j.aca.2024.342346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 01/11/2024] [Accepted: 02/04/2024] [Indexed: 02/26/2024]
Abstract
"MS/MS spectrum to structure" analysis is the most challenging task for MS/MS-relied qualitative characterization. The conventional database- and computation-assisted strategies cannot reach confirmative identification, notably for isomers. Hence, an advanced strategy was proposed here through tackling the two determinant obstacles such as the transformation from elemental compositions to fragment ion structures and the linkage style amongst substructures. As typical conjugated structures, esters were measured for strategy illustration, and metabolite identification of a famous natural antioxidant namely rosmarinic acid (RosA) in rat was undertaken for applicability justification. Through programming online energy-resolved (ER)-MS for the first collision cell of Qtrap-MS device, full collision energy ramp (FCER)-MS2 spectrum was configured for [M-H]- ion of each ester to provide optimal collision energies (OCEs) for all concerned diagnostic fragment ions (DFIs), i.e. a-, b-, c-, y-, and z-type ions. The linear correlations between masses and OCEs were built for each ion type to facilitate DFIs recognition from chaotic MS2 spectrum. To identify 1st-generation fragment ions, full exciting energy ramp (FEER)-MS3 spectra were configured for key DFIs via programming the second ER-MS in the latter collision chamber. FEER-MS3 spectrum of 1st-generation fragment ion for ester was demonstrated to be identical with FEER-MS2 spectrum of certain hydrolysis product when sharing the same structure. After applying the advanced strategy to recognize DFIs and identify 1st-generation fragment ions, a total of forty metabolites (M1-M40), resulted from hydrolysis, methylation, sulfation, and glucuronidation, were unambiguously identified for RosA after oral administration. Together, the advanced bottom-up strategy hyphenating FCER-MS2 and FEER-MS3 spectra, is meaningful to strengthen "MS/MS spectrum to structure" analysis through recognizing and identifying fragment ions.
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Affiliation(s)
- Ke Zhang
- Modern Research Center for Traditional Chinese Medicine, Beijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, East Road of North 3rd Ring, Chaoyang District, Beijing, 100029, China
| | - Han Li
- Modern Research Center for Traditional Chinese Medicine, Beijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, East Road of North 3rd Ring, Chaoyang District, Beijing, 100029, China
| | - Jingjing Shi
- Modern Research Center for Traditional Chinese Medicine, Beijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, East Road of North 3rd Ring, Chaoyang District, Beijing, 100029, China
| | - Wenjing Liu
- School of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, 450046, China
| | - Yitao Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, 999078, Macao
| | - Pengfei Tu
- Modern Research Center for Traditional Chinese Medicine, Beijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, East Road of North 3rd Ring, Chaoyang District, Beijing, 100029, China
| | - Jun Li
- Modern Research Center for Traditional Chinese Medicine, Beijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, East Road of North 3rd Ring, Chaoyang District, Beijing, 100029, China
| | - Yuelin Song
- Modern Research Center for Traditional Chinese Medicine, Beijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, East Road of North 3rd Ring, Chaoyang District, Beijing, 100029, China.
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18
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Silva E, Dantas R, Barbosa JC, Berlinck RGS, Fill T. Metabolomics approach to understand molecular mechanisms involved in fungal pathogen-citrus pathosystems. Mol Omics 2024; 20:154-168. [PMID: 38273771 DOI: 10.1039/d3mo00182b] [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: 01/27/2024]
Abstract
Citrus is a crucial crop with a significant economic impact globally. However, postharvest decay caused by fungal pathogens poses a considerable threat, leading to substantial financial losses. Penicillium digitatum, Penicillium italicum, Geotrichum citri-aurantii and Phyllosticta citricarpa are the main fungal pathogens, causing green mold, blue mold, sour rot and citrus black spot diseases, respectively. The use of chemical fungicides as a control strategy in citrus raises concerns about food and environmental safety. Therefore, understanding the molecular basis of host-pathogen interactions is essential to find safer alternatives. This review highlights the potential of the metabolomics approach in the search for bioactive compounds involved in the pathogen-citrus interaction, and how the integration of metabolomics and genomics contributes to the understanding of secondary metabolites associated with fungal virulence and the fungal infection mechanisms. Our goal is to provide a pipeline combining metabolomics and genomics that can effectively guide researchers to perform studies aiming to contribute to the understanding of the fundamental chemical and biochemical aspects of pathogen-host interactions, in order to effectively develop new alternatives for fungal diseases in citrus cultivation. We intend to inspire the scientific community to question unexplored biological systems, and to employ diverse analytical approaches and metabolomics techniques to address outstanding questions about the non-studied pathosystems from a chemical biology perspective.
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Affiliation(s)
- Evandro Silva
- State University of Campinas, Institute of Chemistry, CEP, 13083-970 Campinas, SP, Brazil.
- University of São Paulo, Institute of Chemistry, CEP 13566-590, São Carlos, SP, Brazil
| | - Rodolfo Dantas
- State University of Campinas, Institute of Chemistry, CEP, 13083-970 Campinas, SP, Brazil.
| | - Júlio César Barbosa
- State University of Campinas, Institute of Chemistry, CEP, 13083-970 Campinas, SP, Brazil.
| | - Roberto G S Berlinck
- University of São Paulo, Institute of Chemistry, CEP 13566-590, São Carlos, SP, Brazil
| | - Taicia Fill
- State University of Campinas, Institute of Chemistry, CEP, 13083-970 Campinas, SP, Brazil.
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19
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Wang M, Yin F, Kong L, Yang L, Sun H, Sun Y, Yan G, Han Y, Wang X. Chinmedomics: a potent tool for the evaluation of traditional Chinese medicine efficacy and identification of its active components. Chin Med 2024; 19:47. [PMID: 38481256 PMCID: PMC10935806 DOI: 10.1186/s13020-024-00917-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 03/03/2024] [Indexed: 03/18/2024] Open
Abstract
As an important part of medical science, Traditional Chinese Medicine (TCM) attracts much public attention due to its multi-target and multi-pathway characteristics in treating diseases. However, the limitations of traditional research methods pose a dilemma for the evaluation of clinical efficacy, the discovery of active ingredients and the elucidation of the mechanism of action. Therefore, innovative approaches that are in line with the characteristics of TCM theory and clinical practice are urgently needed. Chinmendomics, a newly emerging strategy for evaluating the efficacy of TCM, is proposed. This strategy combines systems biology, serum pharmacochemistry of TCM and bioinformatics to evaluate the efficacy of TCM with a holistic view by accurately identifying syndrome biomarkers and monitoring their complex metabolic processes intervened by TCM, and finding the agents associated with the metabolic course of pharmacodynamic biomarkers by constructing a bioinformatics-based correlation network model to further reveal the interaction between agents and pharmacodynamic targets. In this article, we review the recent progress of Chinmedomics to promote its application in the modernisation and internationalisation of TCM.
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Affiliation(s)
- Mengmeng Wang
- State Key Laboratory of Integration and Innovation of Classical Formula and Modern Chinese Medicines, National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Heping Road 24, Harbin, 150040, China
| | - Fengting Yin
- State Key Laboratory of Integration and Innovation of Classical Formula and Modern Chinese Medicines, National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Heping Road 24, Harbin, 150040, China
| | - Ling Kong
- State Key Laboratory of Integration and Innovation of Classical Formula and Modern Chinese Medicines, National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Heping Road 24, Harbin, 150040, China
- State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China
| | - Le Yang
- State Key Laboratory of Dampness Syndrome, The Second Affiliated Hospital Guangzhou University of Chinese Medicine, Dade Road 111, Guangzhou, China
| | - Hui Sun
- State Key Laboratory of Integration and Innovation of Classical Formula and Modern Chinese Medicines, National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Heping Road 24, Harbin, 150040, China.
| | - Ye Sun
- State Key Laboratory of Dampness Syndrome, The Second Affiliated Hospital Guangzhou University of Chinese Medicine, Dade Road 111, Guangzhou, China
| | - Guangli Yan
- State Key Laboratory of Integration and Innovation of Classical Formula and Modern Chinese Medicines, National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Heping Road 24, Harbin, 150040, China
| | - Ying Han
- State Key Laboratory of Integration and Innovation of Classical Formula and Modern Chinese Medicines, National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Heping Road 24, Harbin, 150040, China
| | - Xijun Wang
- State Key Laboratory of Integration and Innovation of Classical Formula and Modern Chinese Medicines, National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Heping Road 24, Harbin, 150040, China.
- State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China.
- State Key Laboratory of Dampness Syndrome, The Second Affiliated Hospital Guangzhou University of Chinese Medicine, Dade Road 111, Guangzhou, China.
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20
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Billing AM, Kim YC, Gullaksen S, Schrage B, Raabe J, Hutzfeldt A, Demir F, Kovalenko E, Lassé M, Dugourd A, Fallegger R, Klampe B, Jaegers J, Li Q, Kravtsova O, Crespo-Masip M, Palermo A, Fenton RA, Hoxha E, Blankenberg S, Kirchhof P, Huber TB, Laugesen E, Zeller T, Chrysopoulou M, Saez-Rodriguez J, Magnussen C, Eschenhagen T, Staruschenko A, Siuzdak G, Poulsen PL, Schwab C, Cuello F, Vallon V, Rinschen MM. Metabolic Communication by SGLT2 Inhibition. Circulation 2024; 149:860-884. [PMID: 38152989 PMCID: PMC10922673 DOI: 10.1161/circulationaha.123.065517] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 11/22/2023] [Indexed: 12/29/2023]
Abstract
BACKGROUND SGLT2 (sodium-glucose cotransporter 2) inhibitors (SGLT2i) can protect the kidneys and heart, but the underlying mechanism remains poorly understood. METHODS To gain insights on primary effects of SGLT2i that are not confounded by pathophysiologic processes or are secondary to improvement by SGLT2i, we performed an in-depth proteomics, phosphoproteomics, and metabolomics analysis by integrating signatures from multiple metabolic organs and body fluids after 1 week of SGLT2i treatment of nondiabetic as well as diabetic mice with early and uncomplicated hyperglycemia. RESULTS Kidneys of nondiabetic mice reacted most strongly to SGLT2i in terms of proteomic reconfiguration, including evidence for less early proximal tubule glucotoxicity and a broad downregulation of the apical uptake transport machinery (including sodium, glucose, urate, purine bases, and amino acids), supported by mouse and human SGLT2 interactome studies. SGLT2i affected heart and liver signaling, but more reactive organs included the white adipose tissue, showing more lipolysis, and, particularly, the gut microbiome, with a lower relative abundance of bacteria taxa capable of fermenting phenylalanine and tryptophan to cardiovascular uremic toxins, resulting in lower plasma levels of these compounds (including p-cresol sulfate). SGLT2i was detectable in murine stool samples and its addition to human stool microbiota fermentation recapitulated some murine microbiome findings, suggesting direct inhibition of fermentation of aromatic amino acids and tryptophan. In mice lacking SGLT2 and in patients with decompensated heart failure or diabetes, the SGLT2i likewise reduced circulating p-cresol sulfate, and p-cresol impaired contractility and rhythm in human induced pluripotent stem cell-derived engineered heart tissue. CONCLUSIONS SGLT2i reduced microbiome formation of uremic toxins such as p-cresol sulfate and thereby their body exposure and need for renal detoxification, which, combined with direct kidney effects of SGLT2i, including less proximal tubule glucotoxicity and a broad downregulation of apical transporters (including sodium, amino acid, and urate uptake), provides a metabolic foundation for kidney and cardiovascular protection.
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Affiliation(s)
- Anja M. Billing
- Departments of Biomedicine (A.M.B., F.D., E.K., J.J., R.A.F., M.C., M.M.R.), Aarhus University, Denmark
| | - Young Chul Kim
- Departments of Medicine and Pharmacology, University of California San Diego, La Jolla (Y.C.K., M.C.-M., V.V.)
- VA San Diego Healthcare System, CA (Y.C.K., M.C.-M., V.V.)
| | - Søren Gullaksen
- Clinical Medicine (S.G., P.L.P.), Aarhus University, Denmark
- Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Denmark (S.G., E.L.)
| | - Benedikt Schrage
- Department of Cardiology, University Heart and Vascular Center Hamburg, Germany (B.S., S.B., P.K., T.Z., C.M.)
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Lübeck, Hamburg, Germany (B.S., J.R., S.B., P.K., T.Z., C.M., T.E., F.C.)
| | - Janice Raabe
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Lübeck, Hamburg, Germany (B.S., J.R., S.B., P.K., T.Z., C.M., T.E., F.C.)
- Institute of Experimental Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (J.R., B.K., T.E., F.C.)
| | - Arvid Hutzfeldt
- III Department of Medicine and Hamburg Center for Kidney Health, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (A.H., M.L., E.H., T.B.H., M.M.R.)
| | - Fatih Demir
- Departments of Biomedicine (A.M.B., F.D., E.K., J.J., R.A.F., M.C., M.M.R.), Aarhus University, Denmark
| | - Elina Kovalenko
- Departments of Biomedicine (A.M.B., F.D., E.K., J.J., R.A.F., M.C., M.M.R.), Aarhus University, Denmark
| | - Moritz Lassé
- III Department of Medicine and Hamburg Center for Kidney Health, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (A.H., M.L., E.H., T.B.H., M.M.R.)
| | - Aurelien Dugourd
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, BioQuant, Heidelberg, Germany (A.D., R.F., J.S.-R.)
| | - Robin Fallegger
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, BioQuant, Heidelberg, Germany (A.D., R.F., J.S.-R.)
| | - Birgit Klampe
- Institute of Experimental Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (J.R., B.K., T.E., F.C.)
| | - Johannes Jaegers
- Departments of Biomedicine (A.M.B., F.D., E.K., J.J., R.A.F., M.C., M.M.R.), Aarhus University, Denmark
| | - Qing Li
- Engineering (Q.L., C.S.), Aarhus University, Denmark
| | - Olha Kravtsova
- Departments of Biomedicine (A.M.B., F.D., E.K., J.J., R.A.F., M.C., M.M.R.), Aarhus University, Denmark
| | - Maria Crespo-Masip
- Departments of Medicine and Pharmacology, University of California San Diego, La Jolla (Y.C.K., M.C.-M., V.V.)
- VA San Diego Healthcare System, CA (Y.C.K., M.C.-M., V.V.)
| | - Amelia Palermo
- Scripps Research, Center for Metabolomics, San Diego, CA (A.P., G.S., M.M.R.)
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (A.P.)
| | - Robert A. Fenton
- Departments of Biomedicine (A.M.B., F.D., E.K., J.J., R.A.F., M.C., M.M.R.), Aarhus University, Denmark
| | - Elion Hoxha
- III Department of Medicine and Hamburg Center for Kidney Health, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (A.H., M.L., E.H., T.B.H., M.M.R.)
| | - Stefan Blankenberg
- Department of Cardiology, University Heart and Vascular Center Hamburg, Germany (B.S., S.B., P.K., T.Z., C.M.)
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Lübeck, Hamburg, Germany (B.S., J.R., S.B., P.K., T.Z., C.M., T.E., F.C.)
| | - Paulus Kirchhof
- Department of Cardiology, University Heart and Vascular Center Hamburg, Germany (B.S., S.B., P.K., T.Z., C.M.)
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Lübeck, Hamburg, Germany (B.S., J.R., S.B., P.K., T.Z., C.M., T.E., F.C.)
- Institute of Cardiovascular Sciences, University of Birmingham, United Kingdom (P.K.)
| | - Tobias B. Huber
- III Department of Medicine and Hamburg Center for Kidney Health, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (A.H., M.L., E.H., T.B.H., M.M.R.)
| | - Esben Laugesen
- Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Denmark (S.G., E.L.)
- Diagnostic Centre, Silkeborg Regional Hospital, Denmark (E.L.)
| | - Tanja Zeller
- Department of Cardiology, University Heart and Vascular Center Hamburg, Germany (B.S., S.B., P.K., T.Z., C.M.)
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Lübeck, Hamburg, Germany (B.S., J.R., S.B., P.K., T.Z., C.M., T.E., F.C.)
| | - Maria Chrysopoulou
- Departments of Biomedicine (A.M.B., F.D., E.K., J.J., R.A.F., M.C., M.M.R.), Aarhus University, Denmark
| | - Julio Saez-Rodriguez
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, BioQuant, Heidelberg, Germany (A.D., R.F., J.S.-R.)
| | - Christina Magnussen
- Department of Cardiology, University Heart and Vascular Center Hamburg, Germany (B.S., S.B., P.K., T.Z., C.M.)
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Lübeck, Hamburg, Germany (B.S., J.R., S.B., P.K., T.Z., C.M., T.E., F.C.)
| | - Thomas Eschenhagen
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Lübeck, Hamburg, Germany (B.S., J.R., S.B., P.K., T.Z., C.M., T.E., F.C.)
- Institute of Experimental Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (J.R., B.K., T.E., F.C.)
| | - Alexander Staruschenko
- Department of Molecular Pharmacology and Physiology, University of South Florida, Tampa (O.K., A.S.)
| | - Gary Siuzdak
- Scripps Research, Center for Metabolomics, San Diego, CA (A.P., G.S., M.M.R.)
| | - Per L. Poulsen
- Clinical Medicine (S.G., P.L.P.), Aarhus University, Denmark
- Steno Diabetes Center (P.L.P.), Aarhus University, Denmark
| | | | - Friederike Cuello
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Lübeck, Hamburg, Germany (B.S., J.R., S.B., P.K., T.Z., C.M., T.E., F.C.)
- Institute of Experimental Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (J.R., B.K., T.E., F.C.)
| | - Volker Vallon
- Departments of Medicine and Pharmacology, University of California San Diego, La Jolla (Y.C.K., M.C.-M., V.V.)
- VA San Diego Healthcare System, CA (Y.C.K., M.C.-M., V.V.)
| | - Markus M. Rinschen
- Departments of Biomedicine (A.M.B., F.D., E.K., J.J., R.A.F., M.C., M.M.R.), Aarhus University, Denmark
- Aarhus Institute of Advanced Studies (M.M.R.), Aarhus University, Denmark
- III Department of Medicine and Hamburg Center for Kidney Health, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (A.H., M.L., E.H., T.B.H., M.M.R.)
- Scripps Research, Center for Metabolomics, San Diego, CA (A.P., G.S., M.M.R.)
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21
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Hu J, Wang SG, Hou Y, Chen Z, Liu L, Li R, Li N, Zhou L, Yang Y, Wang L, Wang L, Yang X, Lei Y, Deng C, Li Y, Deng Z, Ding Y, Kuang Y, Yao Z, Xun Y, Li F, Li H, Hu J, Liu Z, Wang T, Hao Y, Jiao X, Guan W, Tao Z, Ren S, Chen K. Multi-omic profiling of clear cell renal cell carcinoma identifies metabolic reprogramming associated with disease progression. Nat Genet 2024; 56:442-457. [PMID: 38361033 PMCID: PMC10937392 DOI: 10.1038/s41588-024-01662-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 01/10/2024] [Indexed: 02/17/2024]
Abstract
Clear cell renal cell carcinoma (ccRCC) is a complex disease with remarkable immune and metabolic heterogeneity. Here we perform genomic, transcriptomic, proteomic, metabolomic and spatial transcriptomic and metabolomic analyses on 100 patients with ccRCC from the Tongji Hospital RCC (TJ-RCC) cohort. Our analysis identifies four ccRCC subtypes including De-clear cell differentiated (DCCD)-ccRCC, a subtype with distinctive metabolic features. DCCD cancer cells are characterized by fewer lipid droplets, reduced metabolic activity, enhanced nutrient uptake capability and a high proliferation rate, leading to poor prognosis. Using single-cell and spatial trajectory analysis, we demonstrate that DCCD is a common mode of ccRCC progression. Even among stage I patients, DCCD is associated with worse outcomes and higher recurrence rate, suggesting that it cannot be cured by nephrectomy alone. Our study also suggests a treatment strategy based on subtype-specific immune cell infiltration that could guide the clinical management of ccRCC.
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Affiliation(s)
- Junyi Hu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shao-Gang Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yaxin Hou
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhaohui Chen
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lilong Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ruizhi Li
- Shanghai Luming Biotech, Shanghai, China
| | - Nisha Li
- Shanghai Luming Biotech, Shanghai, China
- Shanghai OE Biotech, Shanghai, China
| | - Lijie Zhou
- Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yu Yang
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Liping Wang
- Department of Pathology, Baylor Scott & White Medical Center, Temple, TX, USA
| | - Liang Wang
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiong Yang
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yichen Lei
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Changqi Deng
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhiyao Deng
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuhong Ding
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yingchun Kuang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhipeng Yao
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Xun
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fan Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Heng Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jia Hu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zheng Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tao Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Hao
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuanmao Jiao
- Pennsylvania Cancer and Regenerative Medicine Research Center, Baruch S. Blumberg Institute, Philadelphia, PA, USA
| | - Wei Guan
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Zhen Tao
- Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Tianjin's Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Shancheng Ren
- Department of Urology, Second Affiliated Hospital of Naval Medical University, Shanghai, China.
| | - Ke Chen
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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22
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Alshammari F, Alam MB, Naznin M, Kim S, Lee SH. Optimization, Metabolomic Analysis, Antioxidant Potential andDepigmenting Activity of Polyphenolic Compounds fromUnmature Ajwa Date Seeds ( Phoenix dactylifera L.) Using Ultrasonic-Assisted Extraction. Antioxidants (Basel) 2024; 13:238. [PMID: 38397836 PMCID: PMC10886343 DOI: 10.3390/antiox13020238] [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: 01/19/2024] [Revised: 02/08/2024] [Accepted: 02/12/2024] [Indexed: 02/25/2024] Open
Abstract
This study sought to optimize the ultrasonic-assisted extraction of polyphenolic compounds from unmature Ajwa date seeds (UMS), conduct untargeted metabolite identification and assess antioxidant and depigmenting activities. Response surface methodology (RSM) utilizing the Box-Behnken design (BBD) and artificial neural network (ANN) modeling was applied to optimize extraction conditions, including the ethanol concentration, extraction temperature and time. The determined optimal conditions comprised the ethanol concentration (62.00%), extraction time (29.00 min), and extraction temperature (50 °C). Under these conditions, UMS exhibited total phenolic content (TPC) and total flavonoid content (TFC) values of 77.52 ± 1.55 mgGAE/g and 58.85 ± 1.12 mgCE/g, respectively, with low relative standard deviation (RSD%) and relative standard error (RSE%). High-resolution mass spectrometry analysis unveiled the presence of 104 secondary metabolites in UMS, encompassing phenols, flavonoids, sesquiterpenoids, lignans and fatty acids. Furthermore, UMS demonstrated robust antioxidant activities in various cell-free antioxidant assays, implicating engagement in both hydrogen atom transfer and single electron transfer mechanisms. Additionally, UMS effectively mitigated tert-butyl hydroperoxide (t-BHP)-induced cellular reactive oxygen species (ROS) generation in a concentration-dependent manner. Crucially, UMS showcased the ability to activate mitogen-activated protein kinases (MAPKs) and suppress key proteins including tyrosinase (Tyr), tyrosinase-related protein-1 and -2 (Trp-1 and -2) and microphthalmia-associated transcription factor (MITF), which associated melanin production in MNT-1 cell. In summary, this study not only optimized the extraction process for polyphenolic compounds from UMS but also elucidated its diverse secondary metabolite profile. The observed antioxidant and depigmenting activities underscore the promising applications of UMS in skincare formulations and pharmaceutical developments.
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Affiliation(s)
- Fanar Alshammari
- Department of Food Science and Biotechnology, Graduate School, Kyungpook National University, Daegu 41566, Republic of Korea; (F.A.); (M.B.A.)
| | - Md Badrul Alam
- Department of Food Science and Biotechnology, Graduate School, Kyungpook National University, Daegu 41566, Republic of Korea; (F.A.); (M.B.A.)
- Food and Bio-Industry Research Institute, Inner Beauty/Antiaging Center, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Marufa Naznin
- Department of Chemistry, Kyungpook National University, Daegu 41566, Republic of Korea; (M.N.); (S.K.)
| | - Sunghwan Kim
- Department of Chemistry, Kyungpook National University, Daegu 41566, Republic of Korea; (M.N.); (S.K.)
- Mass Spectroscopy Converging Research and Green-Nano Materials Research Center, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Sang-Han Lee
- Department of Food Science and Biotechnology, Graduate School, Kyungpook National University, Daegu 41566, Republic of Korea; (F.A.); (M.B.A.)
- Food and Bio-Industry Research Institute, Inner Beauty/Antiaging Center, Kyungpook National University, Daegu 41566, Republic of Korea
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23
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van Tetering L, Spies S, Wildeman QDK, Houthuijs KJ, van Outersterp RE, Martens J, Wevers RA, Wishart DS, Berden G, Oomens J. A spectroscopic test suggests that fragment ion structure annotations in MS/MS libraries are frequently incorrect. Commun Chem 2024; 7:30. [PMID: 38355930 PMCID: PMC10867025 DOI: 10.1038/s42004-024-01112-7] [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: 11/18/2023] [Accepted: 01/22/2024] [Indexed: 02/16/2024] Open
Abstract
Modern untargeted mass spectrometry (MS) analyses quickly detect and resolve thousands of molecular compounds. Although features are readily annotated with a molecular formula in high-resolution small-molecule MS applications, the large majority of them remains unidentified in terms of their full molecular structure. Collision-induced dissociation tandem mass spectrometry (CID-MS2) provides a diagnostic molecular fingerprint to resolve the molecular structure through a library search. However, for de novo identifications, one must often rely on in silico generated MS2 spectra as reference. The ability of different in silico algorithms to correctly predict MS2 spectra and thus to retrieve correct molecular structures is a topic of lively debate, for instance in the CASMI contest. Underlying the predicted MS2 spectra are the in silico generated product ion structures, which are normally not used in de novo identification, but which can serve to critically assess the fragmentation algorithms. Here we evaluate in silico generated MSn product ion structures by comparison with structures established experimentally by infrared ion spectroscopy (IRIS). For a set of three dozen product ion structures from five precursor molecules, we find that virtually all fragment ion structure annotations in three major in silico MS2 libraries (HMDB, METLIN, mzCloud) are incorrect and caution the reader against their use for structure annotation of MS/MS ions.
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Affiliation(s)
- Lara van Tetering
- Radboud University, Institute for Molecules and Materials, FELIX Laboratory, Toernooiveld 7, 6525ED, Nijmegen, The Netherlands
| | - Sylvia Spies
- Radboud University, Institute for Molecules and Materials, FELIX Laboratory, Toernooiveld 7, 6525ED, Nijmegen, The Netherlands
| | - Quirine D K Wildeman
- Radboud University, Institute for Molecules and Materials, FELIX Laboratory, Toernooiveld 7, 6525ED, Nijmegen, The Netherlands
| | - Kas J Houthuijs
- Radboud University, Institute for Molecules and Materials, FELIX Laboratory, Toernooiveld 7, 6525ED, Nijmegen, The Netherlands
| | - Rianne E van Outersterp
- Radboud University, Institute for Molecules and Materials, FELIX Laboratory, Toernooiveld 7, 6525ED, Nijmegen, The Netherlands
| | - Jonathan Martens
- Radboud University, Institute for Molecules and Materials, FELIX Laboratory, Toernooiveld 7, 6525ED, Nijmegen, The Netherlands
| | - Ron A Wevers
- Department of Laboratory Medicine, Translational Metabolic Laboratory, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525GA, Nijmegen, The Netherlands
| | - David S Wishart
- Departments of Computing Science and Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Giel Berden
- Radboud University, Institute for Molecules and Materials, FELIX Laboratory, Toernooiveld 7, 6525ED, Nijmegen, The Netherlands
| | - Jos Oomens
- Radboud University, Institute for Molecules and Materials, FELIX Laboratory, Toernooiveld 7, 6525ED, Nijmegen, The Netherlands.
- van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, 1098XH, Amsterdam, The Netherlands.
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24
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Sheng Y, Wang J, Liu S, Jiang Y. IMN4NPD: An Integrated Molecular Networking Workflow for Natural Product Dereplication. Anal Chem 2024. [PMID: 38324659 DOI: 10.1021/acs.analchem.3c04746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Molecular networking has emerged as a standard approach for natural product (NP) discovery. However, the current pipeline based on molecular networks tends to prioritize larger clusters comprising multiple nodes. To address this issue, we present the integrated molecular networking workflow for NP dereplication (IMN4NPD). This approach not only expedites the rapid dereplication of extensive clusters within the molecular network but also places specific emphasis on self-looped or pairs of nodes, which are often overlooked by the current methods. By amalgamating the outputs from various computational tools, we efficiently dereplicate compounds falling into specific categories and provide annotations for both large cluster nodes and self-looped or pair of nodes within the molecular network. Furthermore, we have incorporated several fundamentally distinct similarity algorithms, namely, Spec2Vec and MS2DeepScore, for constructing the t-SNE network. Through comparison with modified cosine similarity, we have observed that integrating additional diverse spectral similarity measures, the resulting t-SNE network enhanced the ability to dereplicate NPs. Demonstrating the use case of an ethanol extract of Plumula nelumbinis, we illustrate that an integration of multiple computational solutions with IMN4NPD aids the dereplication, especially self-looped nodes, and in the discovery of novel compounds in NPs.
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Affiliation(s)
- Yanghao Sheng
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, China
- Institute for Rational and Safe Medication Practices, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Jue Wang
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Shao Liu
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, China
- Institute for Rational and Safe Medication Practices, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Yueping Jiang
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, China
- Institute for Rational and Safe Medication Practices, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
- College of Pharmacy, Changsha Medical University, Changsha 410219, Hunan, China
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25
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Li X, Li C, Chen Z, Wang J, Sun J, Yao J, Chen K, Li Z, Ye H. High-resolution mass spectrometry-based non-targeted metabolomics reveals toxicity of naphthalene on tall fescue and intrinsic molecular mechanisms. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 271:115975. [PMID: 38244514 DOI: 10.1016/j.ecoenv.2024.115975] [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: 08/16/2023] [Revised: 01/08/2024] [Accepted: 01/10/2024] [Indexed: 01/22/2024]
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous at relatively high concentrations by atmospheric deposition, and they are threatening to the environment. In this study, the toxicity of naphthalene on tall fescue and its potential responding mechanism was first studied by integrating approaches. Tall fescue seedlings were exposed to 0, 20, and 100 mg L-1 naphthalene in a hydroponic environment for 9 days, and toxic effects were observed by the studies of general physiological studies, chlorophyll fluorescence, and root morphology. Additionally, Ultra Performance Liquid Chromatography - Electrospray Ionization - High-Resolution Mass Spectrometry (UPLC-ESI-HRMS) was used to depict metabolic profiles of tall fescue under different exposure durations of naphthalene, and the intrinsic molecular mechanism of tall fescue resistance to abiotic stresses. Tall fescue shoots were more sensitive to the toxicity of naphthalene than roots. Low-level exposure to naphthalene inhibited the electron transport from the oxygen-evolving complex (OEC) to D1 protein in tall fescue shoots but induced the growth of roots. Naphthalene induced metabolic change of tall fescue roots in 12 h, and tall fescue roots maintained the level of sphingolipids after long-term exposure to naphthalene, which may play important roles in plant resistance to abiotic stresses.
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Affiliation(s)
- Xuecheng Li
- Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission, College of Resources and Environmental Science, South-Central Minzu University, Wuhan 430074, PR China; College of Pharmacy, South-Central Minzu University, Wuhan 430074, PR China
| | - Changyi Li
- Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission, College of Resources and Environmental Science, South-Central Minzu University, Wuhan 430074, PR China
| | - Ziyu Chen
- Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission, College of Resources and Environmental Science, South-Central Minzu University, Wuhan 430074, PR China; College of Pharmacy, South-Central Minzu University, Wuhan 430074, PR China
| | - Jiahui Wang
- Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission, College of Resources and Environmental Science, South-Central Minzu University, Wuhan 430074, PR China
| | - Jie Sun
- Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission, College of Resources and Environmental Science, South-Central Minzu University, Wuhan 430074, PR China
| | - Jun Yao
- School of Water Resources & Environment, China University of Geosciences Beijing, Beijing, PR China
| | - Ke Chen
- Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission, College of Resources and Environmental Science, South-Central Minzu University, Wuhan 430074, PR China.
| | - Zhenghui Li
- College of Pharmacy, South-Central Minzu University, Wuhan 430074, PR China.
| | - Hengpeng Ye
- Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission, College of Resources and Environmental Science, South-Central Minzu University, Wuhan 430074, PR China.
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26
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Glasser NR, Cui D, Risser DD, Okafor CD, Balskus EP. Accelerating the discovery of alkyl halide-derived natural products using halide depletion. Nat Chem 2024; 16:173-182. [PMID: 38216751 PMCID: PMC10849952 DOI: 10.1038/s41557-023-01390-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 10/30/2023] [Indexed: 01/14/2024]
Abstract
Even in the genomic era, microbial natural product discovery workflows can be laborious and limited in their ability to target molecules with specific structural features. Here we leverage an understanding of biosynthesis to develop a workflow that targets the discovery of alkyl halide-derived natural products by depleting halide anions, a key biosynthetic substrate for enzymatic halogenation, from microbial growth media. By comparing the metabolomes of bacterial cultures grown in halide-replete and deficient media, we rapidly discovered the nostochlorosides, the products of an orphan halogenase-encoding gene cluster from Nostoc punctiforme ATCC 29133. We further found that these products, a family of unusual chlorinated glycolipids featuring the rare sugar gulose, are polymerized via an unprecedented enzymatic etherification reaction. Together, our results highlight the power of leveraging an understanding of biosynthetic logic to streamline natural product discovery.
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Affiliation(s)
- Nathaniel R Glasser
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Dongtao Cui
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Douglas D Risser
- Department of Biology, University of the Pacific, Stockton, CA, USA
| | - C Denise Okafor
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA
- Department of Chemistry, Pennsylvania State University, University Park, PA, USA
| | - Emily P Balskus
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA.
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27
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Chen Q, Lu Q, Zhang L, Zhang C, Zhang J, Gu Y, Huang Q, Tang H. A novel endogenous retention-index for minimizing retention-time variations in metabolomic analysis with reversed-phase ultrahigh-performance liquid-chromatography and mass spectrometry. Talanta 2024; 268:125318. [PMID: 37875029 DOI: 10.1016/j.talanta.2023.125318] [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: 06/06/2023] [Revised: 10/07/2023] [Accepted: 10/14/2023] [Indexed: 10/26/2023]
Abstract
Consistent retention time (tR) of metabolites is vital for identification in metabolomic analysis with ultrahigh-performance liquid-chromatography (UPLC). To minimize inter-experimental tR variations from the reversed-phase UPLC-MS, we developed an endogenous retention-index (endoRI) using in-sample straight-chain acylcarnitines with different chain-length (LC, C0-C26) without additives. The endoRI-corrections reduced the tR variations caused by the combined changes of mobile phases, gradients, flow-rates, elution time, columns and temperature from up to 5.1 min-0.2 min for most metabolites in a model metabolome consisting of 91 metabolites and multiple biological matrices including human serum, plasma, fecal, urine, A549 cells and rabbit liver extracts. The endoRI-corrections also reduced the inter-batch and inter-platform tR variations from 1.5 min to 0.15 min for 95 % of detected features in the above biological samples. We further established a quantitative model between tR and LC for predicting tR values of acylcarnitines when absent in samples. This makes it possible to compare metabolites' tR from different tR databases and the UPLC-based metabolomic data from different batches.
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Affiliation(s)
- Qinsheng Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Qinwei Lu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Lianglong Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Chenhan Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Jingxian Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yu Gu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Qingxia Huang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
| | - Huiru Tang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
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28
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Adeosun WB, Loots DT. Medicinal Plants against Viral Infections: A Review of Metabolomics Evidence for the Antiviral Properties and Potentials in Plant Sources. Viruses 2024; 16:218. [PMID: 38399995 PMCID: PMC10892737 DOI: 10.3390/v16020218] [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: 12/12/2023] [Revised: 01/22/2024] [Accepted: 01/29/2024] [Indexed: 02/25/2024] Open
Abstract
Most plants have developed unique mechanisms to cope with harsh environmental conditions to compensate for their lack of mobility. A key part of their coping mechanisms is the synthesis of secondary metabolites. In addition to their role in plants' defense against pathogens, they also possess therapeutic properties against diseases, and their use by humans predates written history. Viruses are a unique class of submicroscopic agents, incapable of independent existence outside a living host. Pathogenic viruses continue to pose a significant threat to global health, leading to innumerable fatalities on a yearly basis. The use of medicinal plants as a natural source of antiviral agents has been widely reported in literature in the past decades. Metabolomics is a powerful research tool for the identification of plant metabolites with antiviral potentials. It can be used to isolate compounds with antiviral capacities in plants and study the biosynthetic pathways involved in viral disease progression. This review discusses the use of medicinal plants as antiviral agents, with a special focus on the metabolomics evidence supporting their efficacy. Suggestions are made for the optimization of various metabolomics methods of characterizing the bioactive compounds in plants and subsequently understanding the mechanisms of their operation.
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Affiliation(s)
- Wilson Bamise Adeosun
- Human Metabolomics, North-West University, Private Bag X6001, Box 269, Potchefstroom 2531, South Africa;
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29
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An S, Lu M, Wang R, Wang J, Jiang H, Xie C, Tong J, Yu C. Ion entropy and accurate entropy-based FDR estimation in metabolomics. Brief Bioinform 2024; 25:bbae056. [PMID: 38426325 PMCID: PMC10939419 DOI: 10.1093/bib/bbae056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/07/2024] [Accepted: 01/25/2024] [Indexed: 03/02/2024] Open
Abstract
Accurate metabolite annotation and false discovery rate (FDR) control remain challenging in large-scale metabolomics. Recent progress leveraging proteomics experiences and interdisciplinary inspirations has provided valuable insights. While target-decoy strategies have been introduced, generating reliable decoy libraries is difficult due to metabolite complexity. Moreover, continuous bioinformatics innovation is imperative to improve the utilization of expanding spectral resources while reducing false annotations. Here, we introduce the concept of ion entropy for metabolomics and propose two entropy-based decoy generation approaches. Assessment of public databases validates ion entropy as an effective metric to quantify ion information in massive metabolomics datasets. Our entropy-based decoy strategies outperform current representative methods in metabolomics and achieve superior FDR estimation accuracy. Analysis of 46 public datasets provides instructive recommendations for practical application.
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Affiliation(s)
- Shaowei An
- Shandong First Medical University & Central Hospital Affiliated to Shandong First Medical University, 6699 Qingdao Road, Jinan 271016, Shandong, China
- Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang, China
- Fudan University, 220 Handan Road, Shanghai 200433, China
| | - Miaoshan Lu
- Shandong First Medical University & Central Hospital Affiliated to Shandong First Medical University, 6699 Qingdao Road, Jinan 271016, Shandong, China
- Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang, China
- Zhejiang University, 866 Yuhangtang Road, Hangzhou 310009, Zhejiang, China
| | - Ruimin Wang
- Shandong First Medical University & Central Hospital Affiliated to Shandong First Medical University, 6699 Qingdao Road, Jinan 271016, Shandong, China
- Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang, China
- Fudan University, 220 Handan Road, Shanghai 200433, China
| | - Jinyin Wang
- Shandong First Medical University & Central Hospital Affiliated to Shandong First Medical University, 6699 Qingdao Road, Jinan 271016, Shandong, China
- Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang, China
- Zhejiang University, 866 Yuhangtang Road, Hangzhou 310009, Zhejiang, China
| | - Hengxuan Jiang
- Shandong First Medical University & Central Hospital Affiliated to Shandong First Medical University, 6699 Qingdao Road, Jinan 271016, Shandong, China
| | - Cong Xie
- Shandong First Medical University & Central Hospital Affiliated to Shandong First Medical University, 6699 Qingdao Road, Jinan 271016, Shandong, China
| | - Junjie Tong
- Shandong First Medical University & Central Hospital Affiliated to Shandong First Medical University, 6699 Qingdao Road, Jinan 271016, Shandong, China
| | - Changbin Yu
- Shandong First Medical University & Central Hospital Affiliated to Shandong First Medical University, 6699 Qingdao Road, Jinan 271016, Shandong, China
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30
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Zhang J, Zhou Y, Lei J, Liu X, Zhang N, Wu L, Li Y. Retention time prediction and MRM validation reinforce the biomarker identification of LC-MS based phospholipidomics. Analyst 2024; 149:515-527. [PMID: 38078496 DOI: 10.1039/d3an01735d] [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: 01/16/2024]
Abstract
Dysfunctional lipid metabolism plays a crucial role in the development and progression of various diseases. Accurate measurement of lipidomes can help uncover the complex interactions between genes, proteins, and lipids in health and diseases. The prediction of retention time (RT) has become increasingly important in both targeted and untargeted metabolomics. However, the potential impact of RT prediction on targeted LC-MS based lipidomics is still not fully understood. Herein, we propose a simplified workflow for predicting RT in phospholipidomics. Our approach involves utilizing the fatty acyl chain length or carbon-carbon double bond (DB) number in combination with multiple reaction monitoring (MRM) validation. We found that our model's predictive capacity for RT was comparable to that of a publicly accessible program (QSRR Automator). Additionally, MRM validation helped in further mitigating the interference in signal recognition. Using this developed workflow, we conducted phospholipidomics of sorafenib resistant hepatocellular carcinoma (HCC) cell lines, namely MHCC97H and Hep3B. Our findings revealed an abundance of monounsaturated fatty acyl (MUFA) or polyunsaturated fatty acyl (PUFA) phospholipids in these cell lines after developing drug resistance. In both cell lines, a total of 29 lipids were found to be co-upregulated and 5 lipids were co-downregulated. Further validation was conducted on seven of the upregulated lipids using an independent dataset, which demonstrates the potential for translation of the established workflow or the lipid biomarkers.
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Affiliation(s)
- Jiangang Zhang
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing 400030, China.
| | - Yu Zhou
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing 400030, China.
| | - Juan Lei
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing 400030, China.
| | - Xudong Liu
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing 400030, China.
| | - Nan Zhang
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing 400030, China.
| | - Lei Wu
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing 400030, China.
| | - Yongsheng Li
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing 400030, China.
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31
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Raslan MA, Raslan SA, Shehata EM, Mahmoud AS, Viana MVC, Aburjaile F, Barh D, Sabri NA, Azevedo V. Mass Spectrometry Applications to Study Human Microbiome. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1443:87-101. [PMID: 38409417 DOI: 10.1007/978-3-031-50624-6_5] [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: 02/28/2024]
Abstract
Microbiotas are an adaptable component of ecosystems, including human ecology. Microorganisms influence the chemistry of their specialized niche, such as the human gut, as well as the chemistry of distant surroundings, such as other areas of the body. Metabolomics based on mass spectrometry (MS) is one of the primary methods for detecting and identifying small compounds generated by the human microbiota, as well as understanding the functional significance of these microbial metabolites. This book chapter gives basic knowledge on the kinds of untargeted mass spectrometry as well as the data types that may be generated in the context of microbiome study. While data analysis remains a barrier, the emphasis is on data analysis methodologies and integrative analysis, particularly the integration of microbiome sequencing data. Mass spectrometry (MS)-based techniques have resurrected culture methods for studying the human gut microbiota, filling in the gaps left by high-throughput sequencing methods in terms of culturing minor populations.
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Affiliation(s)
| | | | | | - Amr S Mahmoud
- Department of Obstetrics and Gynecology, Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - Marcus Vinicius Canário Viana
- Laboratório de Genética Celular e Molecular, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Flávia Aburjaile
- Preventive Veterinary Medicine Departament, Veterinary School, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Debmalya Barh
- Laboratório de Genética Celular e Molecular, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Institute of Integrative Omics and Applied Biotechnology, Nonakuri, Purba Medinipur, West Bengal, India
| | - Nagwa A Sabri
- Department of Clinical Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt.
| | - Vasco Azevedo
- Laboratório de Genética Celular e Molecular, Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
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32
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Baker ES, Hoang C, Uritboonthai W, Heyman HM, Pratt B, MacCoss M, MacLean B, Plumb R, Aisporna A, Siuzdak G. METLIN-CCS: an ion mobility spectrometry collision cross section database. Nat Methods 2023; 20:1836-1837. [PMID: 37932399 PMCID: PMC10843661 DOI: 10.1038/s41592-023-02078-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Affiliation(s)
- Erin S Baker
- Department of Chemistry, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Corey Hoang
- Scripps Center of Metabolomics and Mass Spectrometry, La Jolla, CA, USA
| | | | - Heino M Heyman
- Bruker Daltonics, Bruker Scientific LLC, Billerica, MA, USA
- Metabolon Inc., Morrisville, NC, USA
| | - Brian Pratt
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Michael MacCoss
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Brendan MacLean
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Robert Plumb
- Waters Corporation, Scientific Operations, IMMERSE, Cambridge, MA, USA
| | - Aries Aisporna
- Scripps Center of Metabolomics and Mass Spectrometry, La Jolla, CA, USA
| | - Gary Siuzdak
- Scripps Center of Metabolomics and Mass Spectrometry, La Jolla, CA, USA.
- Department of Chemistry, Molecular and Computational Biology, Scripps Research Institute, La Jolla, CA, USA.
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33
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Bordag N, Nagy BM, Zügner E, Ludwig H, Foris V, Nagaraj C, Biasin V, Bodenhofer U, Magnes C, Maron BA, Ulrich S, Lange TJ, Hötzenecker K, Pieber T, Olschewski H, Olschewski A. Lipidomics for diagnosis and prognosis of pulmonary hypertension. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.17.23289772. [PMID: 37292870 PMCID: PMC10246148 DOI: 10.1101/2023.05.17.23289772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Background Pulmonary hypertension (PH) poses a significant health threat with high morbidity and mortality, necessitating improved diagnostic tools for enhanced management. Current biomarkers for PH lack functionality and comprehensive diagnostic and prognostic capabilities. Therefore, there is a critical need to develop biomarkers that address these gaps in PH diagnostics and prognosis. Methods To address this need, we employed a comprehensive metabolomics analysis in 233 blood based samples coupled with machine learning analysis. For functional insights, human pulmonary arteries (PA) of idiopathic pulmonary arterial hypertension (PAH) lungs were investigated and the effect of extrinsic FFAs on human PA endothelial and smooth muscle cells was tested in vitro. Results PA of idiopathic PAH lungs showed lipid accumulation and altered expression of lipid homeostasis-related genes. In PA smooth muscle cells, extrinsic FFAs caused excessive proliferation and endothelial barrier dysfunction in PA endothelial cells, both hallmarks of PAH.In the training cohort of 74 PH patients, 30 disease controls without PH, and 65 healthy controls, diagnostic and prognostic markers were identified and subsequently validated in an independent cohort. Exploratory analysis showed a highly impacted metabolome in PH patients and machine learning confirmed a high diagnostic potential. Fully explainable specific free fatty acid (FFA)/lipid-ratios were derived, providing exceptional diagnostic accuracy with an area under the curve (AUC) of 0.89 in the training and 0.90 in the validation cohort, outperforming machine learning results. These ratios were also prognostic and complemented established clinical prognostic PAH scores (FPHR4p and COMPERA2.0), significantly increasing their hazard ratios (HR) from 2.5 and 3.4 to 4.2 and 6.1, respectively. Conclusion In conclusion, our research confirms the significance of lipidomic alterations in PH, introducing innovative diagnostic and prognostic biomarkers. These findings may have the potential to reshape PH management strategies.
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Affiliation(s)
- Natalie Bordag
- Department of Dermatology and Venereology, Medical University of Graz, Graz, Austria
- Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria
- CBmed GmbH, Center for Biomarker Research in Medicine, Graz, Austria
- BioMedTech, Graz, Austria
| | - Bence Miklos Nagy
- Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria
| | - Elmar Zügner
- Institute for Biomedical Research and Technologies (HEALTH), Joanneum Research Forschungsgesellschaft m.b.H, Graz, Austria
| | - Helga Ludwig
- School of Informatics, Communications, and Media, University of Applied Sciences Upper Austria, Hagenberg, Austria
| | - Vasile Foris
- Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria
- Division of Pulmonology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Chandran Nagaraj
- Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria
- BioMedTech, Graz, Austria
| | - Valentina Biasin
- Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria
- Division of Physiology, Otto Loewi Research Centre, Medical University of Graz, Graz, Austria
| | - Ulrich Bodenhofer
- School of Informatics, Communications, and Media, University of Applied Sciences Upper Austria, Hagenberg, Austria
| | - Christoph Magnes
- Institute for Biomedical Research and Technologies (HEALTH), Joanneum Research Forschungsgesellschaft m.b.H, Graz, Austria
| | - Bradley A. Maron
- University of Maryland School of Medicine, Baltimore, MD and The University of Maryland-Institute for Health Computing, Bethesda, MD, USA
| | - Silvia Ulrich
- Clinic of Pulmonology, University and University Hospital of Zurich, Zürich, Switzerland
| | - Tobias J. Lange
- Department of Internal Medicine II, Pulmonology and Critical Care, Kreisklinik Bad Reichenhall, Bad Reichenhall, Germany
- Faculty of Medicine, University of Regensburg, Regensburg, Germany
| | - Konrad Hötzenecker
- Department of Thoracic Surgery, Medical University of Vienna, Vienna, Austria
| | - Thomas Pieber
- CBmed GmbH, Center for Biomarker Research in Medicine, Graz, Austria
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz Austria
- BioMedTech, Graz, Austria
| | - Horst Olschewski
- Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria
- Division of Pulmonology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
- BioMedTech, Graz, Austria
| | - Andrea Olschewski
- Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria
- Experimental Anaesthesiology, Department of Anaesthesiology and Intensive Care Medicine, Medical University of Graz, Graz, Austria
- BioMedTech, Graz, Austria
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Kwon Y, Kwon H, Han J, Kang M, Kim JY, Shin D, Choi YS, Kang S. Retention Time Prediction through Learning from a Small Training Data Set with a Pretrained Graph Neural Network. Anal Chem 2023; 95:17273-17283. [PMID: 37955847 DOI: 10.1021/acs.analchem.3c03177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2023]
Abstract
Graph neural networks (GNNs) have shown remarkable performance in predicting the retention time (RT) for small molecules. However, the training data set for a particular target chromatographic system tends to exhibit scarcity, which poses a challenge because the experimental process for measuring RT is costly. To address this challenge, transfer learning has been used to leverage an abundant training data set from a related source task. In this study, we present an improved transfer learning method to better predict the RT of molecules for a target chromatographic system by learning from a small training data set with a pretrained GNN. We use a graph isomorphism network as the architecture of the GNN. The GNN is pretrained on the METLIN-SMRT data set and is then fine-tuned on the target training data set for a fixed number of training iterations using the limited-memory Broyden-Fletcher-Goldfarb-Shanno optimizer with a learning rate decay. We demonstrate that the proposed method achieves superior predictive performance on various chromatographic systems compared with that of the existing transfer learning methods, especially when only a small training data set is available for use. A potential avenue for future research is to leverage multiple small training data sets from different chromatographic systems to further enhance the generalization performance.
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Affiliation(s)
- Youngchun Kwon
- Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Suwon 16678, Republic of Korea
| | - Hyukju Kwon
- Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Suwon 16678, Republic of Korea
- Department of Chemistry, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| | - Jongmin Han
- Department of Industrial Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| | - Myeonginn Kang
- Department of Industrial Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| | - Ji-Yeong Kim
- Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Suwon 16678, Republic of Korea
| | - Dongyeeb Shin
- Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Suwon 16678, Republic of Korea
| | - Youn-Suk Choi
- Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Suwon 16678, Republic of Korea
| | - Seokho Kang
- Department of Industrial Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
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35
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Lieng B, Quaile AT, Domingo-Almenara X, Röst HL, Montenegro-Burke JR. Computational Expansion of High-Resolution-MS n Spectral Libraries. Anal Chem 2023; 95:17284-17291. [PMID: 37963318 PMCID: PMC10688228 DOI: 10.1021/acs.analchem.3c03343] [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: 07/27/2023] [Revised: 10/31/2023] [Accepted: 10/31/2023] [Indexed: 11/16/2023]
Abstract
Commonly, in MS-based untargeted metabolomics, some metabolites cannot be confidently identified due to ambiguities in resolving isobars and structurally similar species. To address this, analytical techniques beyond traditional MS2 analysis, such as MSn fragmentation, can be applied to probe metabolites for additional structural information. In MSn fragmentation, recursive cycles of activation are applied to fragment ions originating from the same precursor ion detected on an MS1 spectrum. This resonant-type collision-activated dissociation (CAD) can yield information that cannot be ascertained from MS2 spectra alone, which helps improve the performance of metabolite identification workflows. However, most approaches for metabolite identification require mass-to-charge (m/z) values measured with high resolution, as this enables the determination of accurate mass values. Unfortunately, high-resolution-MSn spectra are relatively rare in spectral libraries. Here, we describe a computational approach to generate a database of high-resolution-MSn spectra by converting existing low-resolution-MSn spectra using complementary high-resolution-MS2 spectra generated by beam-type CAD. Using this method, we have generated a database, derived from the NIST20 MS/MS database, of MSn spectral trees representing 9637 compounds and 19386 precursor ions where at least 90% of signal intensity was converted from low-to-high resolution.
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Affiliation(s)
- Brandon
Y. Lieng
- Terrence
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S
3E1, Canada
- Department
of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute
of Biomedical Engineering, University of
Toronto, Toronto, ON M5S 3G9, Canada
| | - Andrew T. Quaile
- Terrence
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S
3E1, Canada
- Department
of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute
of Biomedical Engineering, University of
Toronto, Toronto, ON M5S 3G9, Canada
| | - Xavier Domingo-Almenara
- Centre
for Omics Sciences, Eurecat—Technology Centre of Catalonia
& Rovira i Virgili University Joint Unit, Reus 43204, Catalonia, Spain
- Department of Electrical, Electronic and Control
Engineering, Universitat Rovira i Virgili, Tarragona 43007, Catalonia, Spain
| | - Hannes L. Röst
- Terrence
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S
3E1, Canada
- Department
of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - J. Rafael Montenegro-Burke
- Terrence
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S
3E1, Canada
- Department
of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute
of Biomedical Engineering, University of
Toronto, Toronto, ON M5S 3G9, Canada
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36
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Kong F, Keshet U, Shen T, Rodriguez E, Fiehn O. LibGen: Generating High Quality Spectral Libraries of Natural Products for EAD-, UVPD-, and HCD-High Resolution Mass Spectrometers. Anal Chem 2023; 95:16810-16818. [PMID: 37939222 DOI: 10.1021/acs.analchem.3c02263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Compound annotation using spectral-matching algorithms is vital for (MS/MS)-based metabolomics research, but is hindered by the lack of high-quality reference MS/MS library spectra. Finding and removing errors from libraries, including noise ions, is mostly done manually. This process is both error-prone and time-consuming. To address these challenges, we have developed an automated library curation pipeline, LibGen, to universally build novel spectral libraries. This pipeline corrects mass errors, denoises spectra by subformula assignments, and performs quality control of the reference spectra by calculating explained intensity and spectral entropy. We employed LibGen to generate three high-quality libraries with chemical standards of 2241 natural products. To this end, we used an IQ-X orbital ion trap mass spectrometer to generate 1947 classic high-energy collision dissociation spectra (HCD) as well as 1093 ultraviolet-photodissociation (UVPD) mass spectra. The third library was generated by an electron-activated collision dissociation (EAD) 7600 ZenoTOF mass spectrometer yielding 3244 MS/MS spectra. The natural compounds covered 140 chemical classes from prenol lipids to benzypyrans with >97% of the compounds showing <0.2 Tanimoto-similarity, demonstrating a very high structural variance. Mass spectra showed much higher information content for both UVPD- and EAD-mass spectra compared to classic HCD spectra when using spectral entropy calculations. We validated the denoising algorithm by acquiring MS/MS spectra at high concentration and at 13-fold diluted chemical standards. At low concentrations, a higher proportion of spectra showed apparent fragment ions that could not be explained by subformula losses of the parent molecule. When more than 10% of the total intensity of MS/MS fragments was regarded as noise ions, spectra were considered as low quality and were not included in the libraries. As the overall process is fully automated, LibGen can be utilized by all researchers who create or curate mass spectral libraries. The libraries we created here are publicly available at MassBank.us.
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Affiliation(s)
- Fanzhou Kong
- Chemistry Department, One Shields Avenue, University of California-Davis, Davis, California 95616, United States
- West Coast Metabolomics Center, University of California-Davis, Davis, California 95616, United States
| | - Uri Keshet
- West Coast Metabolomics Center, University of California-Davis, Davis, California 95616, United States
| | - Tong Shen
- West Coast Metabolomics Center, University of California-Davis, Davis, California 95616, United States
| | - Elys Rodriguez
- Chemistry Department, One Shields Avenue, University of California-Davis, Davis, California 95616, United States
- West Coast Metabolomics Center, University of California-Davis, Davis, California 95616, United States
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California-Davis, Davis, California 95616, United States
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37
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Murray KJ, Villalta PW, Griffin TJ, Balbo S. Discovery of Modified Metabolites, Secondary Metabolites, and Xenobiotics by Structure-Oriented LC-MS/MS. Chem Res Toxicol 2023; 36:1666-1682. [PMID: 37862059 DOI: 10.1021/acs.chemrestox.3c00209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
Exogenous compounds and metabolites derived from therapeutics, microbiota, or environmental exposures directly interact with endogenous metabolic pathways, influencing disease pathogenesis and modulating outcomes of clinical interventions. With few spectral library references, the identification of covalently modified biomolecules, secondary metabolites, and xenobiotics is a challenging task using global metabolomics profiling approaches. Numerous liquid chromatography-coupled mass spectrometry (LC-MS) small molecule analytical workflows have been developed to curate global profiling experiments for specific compound groups of interest. These workflows exploit shared structural moiety, functional groups, or elemental composition to discover novel and undescribed compounds through nontargeted small molecule discovery pipelines. This Review introduces the concept of structure-oriented LC-MS discovery methodology and aims to highlight common approaches employed for the detection and characterization of covalently modified biomolecules, secondary metabolites, and xenobiotics. These approaches represent a combination of instrument-dependent and computational techniques to rapidly curate global profiling experiments to detect putative ions of interest based on fragmentation patterns, predictable phase I or phase II metabolic transformations, or rare elemental composition. Application of these methods is explored for the detection and identification of novel and undescribed biomolecules relevant to the fields of toxicology, pharmacology, and drug discovery. Continued advances in these methods expand the capacity for selective compound discovery and characterization that promise remarkable insights into the molecular interactions of exogenous chemicals with host biochemical pathways.
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Affiliation(s)
- Kevin J Murray
- Department of Biochemistry, Molecular Biology, and Biophysics, College of Biological Science, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Peter W Villalta
- Department of Medicinal Chemistry, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota 55455, United States
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Timothy J Griffin
- Department of Biochemistry, Molecular Biology, and Biophysics, College of Biological Science, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Silvia Balbo
- Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455, United States
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota 55455, United States
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38
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Shastry A, Dunham-Snary K. Metabolomics and mitochondrial dysfunction in cardiometabolic disease. Life Sci 2023; 333:122137. [PMID: 37788764 DOI: 10.1016/j.lfs.2023.122137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/21/2023] [Accepted: 09/29/2023] [Indexed: 10/05/2023]
Abstract
Circulating metabolites are indicators of systemic metabolic dysfunction and can be detected through contemporary techniques in metabolomics. These metabolites are involved in numerous mitochondrial metabolic processes including glycolysis, fatty acid β-oxidation, and amino acid catabolism, and changes in the abundance of these metabolites is implicated in the pathogenesis of cardiometabolic diseases (CMDs). Epigenetic regulation and direct metabolite-protein interactions modulate metabolism, both within cells and in the circulation. Dysfunction of multiple mitochondrial components stemming from mitochondrial DNA mutations are implicated in disease pathogenesis. This review will summarize the current state of knowledge regarding: i) the interactions between metabolites found within the mitochondrial environment during CMDs, ii) various metabolites' effects on cellular and systemic function, iii) how harnessing the power of metabolomic analyses represents the next frontier of precision medicine, and iv) how these concepts integrate to expand the clinical potential for translational cardiometabolic medicine.
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Affiliation(s)
- Abhishek Shastry
- Department of Medicine, Queen's University, Kingston, ON, Canada
| | - Kimberly Dunham-Snary
- Department of Medicine, Queen's University, Kingston, ON, Canada; Department of Biomedical & Molecular Sciences, Queen's University, Kingston, ON, Canada.
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39
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Hu G, Qiu M. Machine learning-assisted structure annotation of natural products based on MS and NMR data. Nat Prod Rep 2023; 40:1735-1753. [PMID: 37519196 DOI: 10.1039/d3np00025g] [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: 08/01/2023]
Abstract
Covering: up to March 2023Machine learning (ML) has emerged as a popular tool for analyzing the structures of natural products (NPs). This review presents a summary of the recent advancements in ML-assisted mass spectrometry (MS) and nuclear magnetic resonance (NMR) data analysis to establish the chemical structures of NPs. First, ML-based MS/MS analyses that rely on library matching are discussed, which involves the utilization of ML algorithms to calculate similarity, predict the MS/MS fragments, and form molecular fingerprint. Then, ML assisted MS/MS structural annotation without library matching is reviewed. Furthermore, the cases of ML algorithms in assisting structural studies of NPs based on NMR are discussed from four perspectives: NMR prediction, functional group identification, structural categorization and quantum chemical calculation. Finally, the review concludes with a discussion of the challenges and the trends associated with the structural establishment of NPs based on ML algorithms.
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Affiliation(s)
- Guilin Hu
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, Yunnan, China.
- University of the Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Minghua Qiu
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, Yunnan, China.
- University of the Chinese Academy of Sciences, Beijing 100049, People's Republic of China
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40
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Schneider TD, Kraemer T, Steuer AE. Untargeted Metabolomics Profiling for Determination of the Time since Deposition of Biofluids in a Forensic Context: A Proof-of-Concept for Urine, Saliva, and Semen in Addition to Blood. Anal Chem 2023; 95:16575-16584. [PMID: 37902306 DOI: 10.1021/acs.analchem.3c02707] [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: 10/31/2023]
Abstract
In a criminal trial, the reconstruction of a crime is one of the fundamental steps of the prosecution process. Common questions, such as what happened, where and how it happened, and who made it happen, need to be solved. Biological evidence at crime scenes can be crucial in the determination of these fundamental questions. One of the more challenging riddles to solve is the when? A trace left at a crime scene can prove a person's presence at the crime scene. Knowledge about when it was deposited there, the time since deposition (TsD), would allow linking the person in space and time to the site. This could fortify allegations against a suspect or discharge accusations if proven to be outside of the temporal boundaries where a suspected crime had occurred. Determining the TsD has yet to become routine forensic casework, despite recent research efforts, especially for blood traces. However, next to blood, other biological traces are also commonly encountered in crime scenes. We here present a study to profile the metabolomes of artificially aged dried body fluid spots of blood, semen, saliva, and urine over 4 weeks by liquid chromatography high-resolution mass spectrometry and data-dependent acquisition. All four body fluids (BFs) exhibited diverse time-dependent changes, and a large number of molecular features (MF) were associated with TsD. Still, significant differences between the BFs were observed, limiting universal interpretability independent of the BF and facilitating a need to further study time-dependent changes of different BFs individually toward the goal of TsD estimation.
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Affiliation(s)
- Tom D Schneider
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, 8057 Zurich, Switzerland
| | - Thomas Kraemer
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, 8057 Zurich, Switzerland
| | - Andrea E Steuer
- Department of Forensic Pharmacology and Toxicology, Zurich Institute of Forensic Medicine, University of Zurich, 8057 Zurich, Switzerland
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Palermo A, Li S, Ten Hoeve J, Chellappa A, Morris A, Dillon B, Ma F, Wang Y, Cao E, Shabane B, Acín-Perez R, Petcherski A, Lusis AJ, Hazen S, Shirihai OS, Pellegrini M, Arumugaswami V, Graeber TG, Deb A. A ketogenic diet can mitigate SARS-CoV-2 induced systemic reprogramming and inflammation. Commun Biol 2023; 6:1115. [PMID: 37923961 PMCID: PMC10624922 DOI: 10.1038/s42003-023-05478-7] [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: 07/06/2023] [Accepted: 10/17/2023] [Indexed: 11/06/2023] Open
Abstract
The ketogenic diet (KD) has demonstrated benefits in numerous clinical studies and animal models of disease in modulating the immune response and promoting a systemic anti-inflammatory state. Here we investigate the effects of a KD on systemic toxicity in mice following SARS-CoV-2 infection. Our data indicate that under KD, SARS-CoV-2 reduces weight loss with overall improved animal survival. Muted multi-organ transcriptional reprogramming and metabolism rewiring suggest that a KD initiates and mitigates systemic changes induced by the virus. We observed reduced metalloproteases and increased inflammatory homeostatic protein transcription in the heart, with decreased serum pro-inflammatory cytokines (i.e., TNF-α, IL-15, IL-22, G-CSF, M-CSF, MCP-1), metabolic markers of inflammation (i.e., kynurenine/tryptophane ratio), and inflammatory prostaglandins, indicative of reduced systemic inflammation in animals infected under a KD. Taken together, these data suggest that a KD can alter the transcriptional and metabolic response in animals following SARS-CoV-2 infection with improved mice health, reduced inflammation, and restored amino acid, nucleotide, lipid, and energy currency metabolism.
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Affiliation(s)
- Amelia Palermo
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- California Nanosystems Institute, University of California, Los Angeles, CA, 90095, USA
- UCLA Metabolomics Center, University of California, Los Angeles, CA, 90095, USA
- Crump Institute for Molecular Imaging, University of California, Los Angeles, CA, 90095, USA
| | - Shen Li
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- UCLA Cardiovascular Research Theme, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Department of Molecular, Cell and Developmental Biology, Division of Life Sciences, University of California, Los Angeles, CA, 90095, USA
- Eli & Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, CA, 90095, USA
- Department of Genetics, David Geffen School of Medicine, Los Angeles, CA, 90095, USA
| | - Johanna Ten Hoeve
- California Nanosystems Institute, University of California, Los Angeles, CA, 90095, USA
- UCLA Metabolomics Center, University of California, Los Angeles, CA, 90095, USA
- Crump Institute for Molecular Imaging, University of California, Los Angeles, CA, 90095, USA
| | - Akshay Chellappa
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Alexandra Morris
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Barbara Dillon
- Department of Environment, Health and Safety, University of California, Los Angeles, CA, 90095, USA
| | - Feiyang Ma
- Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, 48109, USA
| | - Yijie Wang
- UCLA Cardiovascular Research Theme, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Department of Molecular, Cell and Developmental Biology, Division of Life Sciences, University of California, Los Angeles, CA, 90095, USA
- Eli & Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, CA, 90095, USA
- Department of Genetics, David Geffen School of Medicine, Los Angeles, CA, 90095, USA
| | - Edward Cao
- UCLA Cardiovascular Research Theme, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Department of Molecular, Cell and Developmental Biology, Division of Life Sciences, University of California, Los Angeles, CA, 90095, USA
- Eli & Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, CA, 90095, USA
- Department of Genetics, David Geffen School of Medicine, Los Angeles, CA, 90095, USA
| | - Byourak Shabane
- Department of Medicine, Endocrinology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Rebeca Acín-Perez
- Department of Medicine, Endocrinology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Anton Petcherski
- Department of Medicine, Endocrinology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - A Jake Lusis
- California Nanosystems Institute, University of California, Los Angeles, CA, 90095, USA
- UCLA Cardiovascular Research Theme, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Stanley Hazen
- Department of Cardiovascular and Metabolic Sciences, Cleveland Clinic, Cleveland, OH, 44195, USA
| | - Orian S Shirihai
- California Nanosystems Institute, University of California, Los Angeles, CA, 90095, USA
- Department of Medicine, Endocrinology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, Division of Life Sciences, University of California, Los Angeles, CA, 90095, USA
- Eli & Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, CA, 90095, USA
| | - Vaithilingaraja Arumugaswami
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Eli & Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, 90095, USA
| | - Thomas G Graeber
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.
- California Nanosystems Institute, University of California, Los Angeles, CA, 90095, USA.
- UCLA Metabolomics Center, University of California, Los Angeles, CA, 90095, USA.
- Crump Institute for Molecular Imaging, University of California, Los Angeles, CA, 90095, USA.
- Eli & Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, 90095, USA.
| | - Arjun Deb
- California Nanosystems Institute, University of California, Los Angeles, CA, 90095, USA.
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.
- UCLA Cardiovascular Research Theme, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.
- Department of Molecular, Cell and Developmental Biology, Division of Life Sciences, University of California, Los Angeles, CA, 90095, USA.
- Eli & Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, 90095, USA.
- Molecular Biology Institute, University of California, Los Angeles, CA, 90095, USA.
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Clarke ED, Ferguson JJ, Stanford J, Collins CE. Dietary Assessment and Metabolomic Methodologies in Human Feeding Studies: A Scoping Review. Adv Nutr 2023; 14:1453-1465. [PMID: 37604308 PMCID: PMC10721540 DOI: 10.1016/j.advnut.2023.08.010] [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: 11/24/2022] [Revised: 05/01/2023] [Accepted: 08/16/2023] [Indexed: 08/23/2023] Open
Abstract
Dietary metabolomics is a relatively objective approach to identifying new biomarkers of dietary intake and for use alongside traditional methods. However, methods used across dietary feeding studies vary, thus making it challenging to compare results. The objective of this study was to synthesize methodological components of controlled human feeding studies designed to quantify the diet-related metabolome in biospecimens, including plasma, serum, and urine after dietary interventions. Six electronic databases were searched. Included studies were as follows: 1) conducted in healthy adults; 2) intervention studies; 3) feeding studies focusing on dietary patterns; and 4) measured the dietary metabolome. From 12,425 texts, 50 met all inclusion criteria. Interventions were primarily crossover (n = 25) and parallel randomized controlled trials (n = 22), with between 8 and 395 participants. Seventeen different dietary patterns were tested, with the most common being the "High versus Low-Glycemic Index/Load" pattern (n = 11) and "Typical Country Intake" (n = 11); with 32 providing all or the majority (90%) of food, 16 providing some food, and 2 providing no food. Metabolites were identified in urine (n = 31) and plasma/serum (n = 30). Metabolites were quantified using liquid chromatography, mass spectroscopy (n = 31) and used untargeted metabolomics (n = 37). There was extensive variability in the methods used in controlled human feeding studies examining the metabolome, including dietary patterns tested, biospecimen sample collection, and metabolomic analysis techniques. To improve the comparability and reproducibility of controlled human feeding studies examining the metabolome, it is important to provide detailed information about the dietary interventions being tested, including information about included or restricted foods, food groups, and meal plans provided. Strategies to control for individual variability, such as a crossover study design, statistical adjustment methods, dietary-controlled run-in periods, or providing standardized meals or test foods throughout the study should also be considered. The protocol for this review has been registered at Open Science Framework (https://doi.org/10.17605/OSF.IO/DAHGS).
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Affiliation(s)
- Erin D Clarke
- School of Health Sciences, College of Health Medicine and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia; Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Jessica Ja Ferguson
- School of Health Sciences, College of Health Medicine and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia; Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Jordan Stanford
- School of Health Sciences, College of Health Medicine and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia; Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Clare E Collins
- School of Health Sciences, College of Health Medicine and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia; Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia.
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Hann EC, Harland-Dunaway M, Garcia AJ, Meuser JE, Jinkerson RE. Alternative carbon sources for the production of plant cellular agriculture: a case study on acetate. FRONTIERS IN PLANT SCIENCE 2023; 14:1104751. [PMID: 37954996 PMCID: PMC10639172 DOI: 10.3389/fpls.2023.1104751] [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: 11/22/2022] [Accepted: 08/09/2023] [Indexed: 11/14/2023]
Abstract
Plant cellular agriculture aims to disrupt the way plant derived products are produced. Plant cell cultures are typically grown with sucrose as the primary carbon and energy source, but alternative carbon sources may have advantages over sucrose including less strain on food systems, lower costs, and more sustainable sourcing. Here we review carbon and energy sources that may serve as alternatives to sucrose in the cultivation of plant cell cultures. We identified acetate as a promising candidate and took the first steps to evaluate its potential for use in growing tobacco plant cell cultures. When added to media containing sucrose, acetate concentrations above 8 mM completely inhibit growth. Lower concentrations of acetate (2-4 mM) can support an increase in dry weight without sucrose but do not provide enough energy for substantial growth. 13C labeling indicates that tobacco plant cell cultures can incorporate carbon from exogenous acetate into proteins and carbohydrates. Analysis of transcriptome data showed that genes encoding glyoxylate cycle enzymes are expressed at very low levels compared to genes from the TCA cycle and glycolysis. Adaptive laboratory evolution experiments were able to increase tobacco cell cultures tolerance to acetate, demonstrating the potential for this type of approach going forward. Overall, our results indicate that acetate can be metabolized by plant cell cultures and suggest that further adaptive laboratory evolution or strain engineering efforts may enable acetate to serve as a sole carbon and energy source for tobacco plant cell cultures. This assessment of acetate provides a framework for evaluating other carbon and energy sources for plant cell cultures, efforts that will help reduce the costs and environmental impact, and increase the commercial potential of plant cellular agriculture.
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Affiliation(s)
- Elizabeth C. Hann
- Center for Industrial Biotechnology, Department of Chemical and Environmental Engineering, University of California, Riverside, Riverside, CA, United States
- Center for Plant Cell Biology, Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA, United States
| | - Marcus Harland-Dunaway
- Center for Industrial Biotechnology, Department of Chemical and Environmental Engineering, University of California, Riverside, Riverside, CA, United States
- Center for Plant Cell Biology, Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA, United States
| | - Adrian J. Garcia
- Center for Industrial Biotechnology, Department of Chemical and Environmental Engineering, University of California, Riverside, Riverside, CA, United States
- Center for Plant Cell Biology, Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA, United States
| | | | - Robert E. Jinkerson
- Center for Industrial Biotechnology, Department of Chemical and Environmental Engineering, University of California, Riverside, Riverside, CA, United States
- Center for Plant Cell Biology, Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA, United States
- Chi Botanic, Alameda, CA, United States
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Rodríguez VM, Velasco P, Cartea ME, Poveda J. Systemic biochemical changes in pepper (Capsicum annuum L.) against Rhizoctonia solani by kale (Brassica oleracea var. acephala L.) green manure application. BMC PLANT BIOLOGY 2023; 23:515. [PMID: 37880578 PMCID: PMC10601221 DOI: 10.1186/s12870-023-04525-z] [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: 05/24/2023] [Accepted: 10/14/2023] [Indexed: 10/27/2023]
Abstract
BACKGROUND In the search for new alternatives to avoid the problems associated with the use of synthetic chemical fungicides in agriculture, the use of green manure (GrM) could help combat fungal diseases of crops, such as those produced by the necrotrophic pathogen Rhizoctonia solani. In the case of the use of Brassica tissues as GrM, it could have an elicitor capacity for systemic plant resistance. RESULTS We used kale leaves as a GrM and applied it to pepper plants infected with R. solani. The application of freeze-dried kale tissues to the roots of pepper plants produced a systemic activation of foliar defences via the salicylic acid (SA) and ethylene (ET) pathways, significantly reducing pathogen damage. In addition, this systemic response led to the accumulation of secondary defence metabolites, such as pipecolic acid, hydroxycoumarin and gluconic acid, in leaves. Remarkably, pepper plants treated with lyophilised kale GrM accumulated glucosinolates when infected with R. solani. We also confirmed that autoclaving removed part of the glucobrassicin (85%) and sinigrin (19%) content of the kale tissues. CONCLUSIONS GrM kale tissues can activate systemic defences in bell pepper against foliar pathogens through SA/ET hormonal pathways, accumulating secondary defence metabolites.
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Affiliation(s)
- Víctor M Rodríguez
- Group of Genetics, Breeding and Biochemistry of Brassicas. Mision Biologica de Galicia (MBG-CSIC), Pontevedra, 36143, Spain
| | - Pablo Velasco
- Group of Genetics, Breeding and Biochemistry of Brassicas. Mision Biologica de Galicia (MBG-CSIC), Pontevedra, 36143, Spain.
| | - María Elena Cartea
- Group of Genetics, Breeding and Biochemistry of Brassicas. Mision Biologica de Galicia (MBG-CSIC), Pontevedra, 36143, Spain
| | - Jorge Poveda
- Recognized Research Group AGROBIOTECH, Consolidated Research Unit 370 (JCyL), Department of Plant Production and Forest Resources, Higher Technical School of Agricultural Engineering of Palencia, University Institute for Research in Sustainable Forest Management (iuFOR), University of Valladolid, Avda. Madrid 57, Palencia, 34004, Spain.
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45
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Wohlgemuth R. Synthesis of Metabolites and Metabolite-like Compounds Using Biocatalytic Systems. Metabolites 2023; 13:1097. [PMID: 37887422 PMCID: PMC10608848 DOI: 10.3390/metabo13101097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 10/13/2023] [Accepted: 10/15/2023] [Indexed: 10/28/2023] Open
Abstract
Methodologies for the synthesis and purification of metabolites, which have been developed following their discovery, analysis, and structural identification, have been involved in numerous life science milestones. The renewed focus on the small molecule domain of biological cells has also created an increasing awareness of the rising gap between the metabolites identified and the metabolites which have been prepared as pure compounds. The design and engineering of resource-efficient and straightforward synthetic methodologies for the production of the diverse and numerous metabolites and metabolite-like compounds have attracted much interest. The variety of metabolic pathways in biological cells provides a wonderful blueprint for designing simplified and resource-efficient synthetic routes to desired metabolites. Therefore, biocatalytic systems have become key enabling tools for the synthesis of an increasing number of metabolites, which can then be utilized as standards, enzyme substrates, inhibitors, or other products, or for the discovery of novel biological functions.
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Affiliation(s)
- Roland Wohlgemuth
- MITR, Institute of Applied Radiation Chemistry, Faculty of Chemistry, Lodz University of Technology, Zeromskiego Street 116, 90-924 Lodz, Poland;
- Swiss Coordination Committee Biotechnology (SKB), 8021 Zurich, Switzerland
- European Society of Applied Biocatalysis (ESAB), 1000 Brussels, Belgium
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46
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Zhu M, He J, Xu Y, Zuo Y, Zhou W, Yue Z, Shao X, Cheng J, Wang T, Mou S. AMPK activation coupling SENP1-Sirt3 axis protects against acute kidney injury. Mol Ther 2023; 31:3052-3066. [PMID: 37608549 PMCID: PMC10556228 DOI: 10.1016/j.ymthe.2023.08.014] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 07/24/2023] [Accepted: 08/18/2023] [Indexed: 08/24/2023] Open
Abstract
Acute kidney injury (AKI) is a critical clinical condition that causes kidney fibrosis, and it currently lacks specific treatment options. In this research, we investigate the role of the SENP1-Sirt3 signaling pathway and its correlation with mitochondrial dysfunction in proximal tubular epithelial cells (PTECs) using folic acid (FA) and ischemia-reperfusion-induced (IRI) AKI models. Our findings reveal that Sirt3 SUMOylation site mutation (Sirt3 KR) or pharmacological stimulation (metformin) protected mice against AKI and subsequent kidney inflammation and fibrosis by decreasing the acetylation level of mitochondrial SOD2, reducing mitochondrial reactive oxygen species (mtROS), and subsequently restoring mitochondrial ATP level, reversing mitochondrial morphology and alleviating cell apoptosis. In addition, AKI in mice was similarly alleviated by reducing mtROS levels using N-acetyl-L-cysteine (NAC) or MitoQ. Metabolomics analysis further demonstrated an increase in antioxidants and metabolic shifts in Sirt3 KR mice during AKI, compared with Sirt3 wild-type (WT) mice. Activation of the AMPK pathway using metformin promoted the SENP1-Sirt3 axis and protected PTECs from apoptosis. Hence, the augmented deSUMOylation of Sirt3 in mitochondria, activated through the metabolism-related AMPK pathway, protects against AKI and subsequently mitigated renal inflammation and fibrosis through Sirt3-SOD2-mtROS, which represents a potential therapeutic target for AKI.
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Affiliation(s)
- Minyan Zhu
- Department of Nephrology, Molecular Cell Lab for Kidney Disease, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 201207, China
| | - Jianli He
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yao Xu
- Department of Nephrology, Molecular Cell Lab for Kidney Disease, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 201207, China
| | - Yong Zuo
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Wenyan Zhou
- Department of Nephrology, Molecular Cell Lab for Kidney Disease, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 201207, China
| | - Zhiying Yue
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xinghua Shao
- Department of Nephrology, Molecular Cell Lab for Kidney Disease, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 201207, China
| | - Jinke Cheng
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Tianshi Wang
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
| | - Shan Mou
- Department of Nephrology, Molecular Cell Lab for Kidney Disease, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 201207, China.
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Zhao X, Stein KR, Chen V, Griffin ME, Lairson LL, Hang HC. Chemoproteomics reveals microbiota-derived aromatic monoamine agonists for GPRC5A. Nat Chem Biol 2023; 19:1205-1214. [PMID: 37248411 DOI: 10.1038/s41589-023-01328-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 04/06/2023] [Indexed: 05/31/2023]
Abstract
The microbiota generates diverse metabolites to modulate host physiology and disease, but their protein targets and mechanisms of action have not been fully elucidated. To address this challenge, we explored microbiota-derived indole metabolites and developed photoaffinity chemical reporters for proteomic studies. We identified many potential indole metabolite-interacting proteins, including metabolic enzymes, transporters, immune sensors and G protein-coupled receptors. Notably, we discovered that aromatic monoamines can bind the orphan receptor GPRC5A and stimulate β-arrestin recruitment. Metabolomic and functional profiling also revealed specific amino acid decarboxylase-expressing microbiota species that produce aromatic monoamine agonists for GPRC5A-β-arrestin recruitment. Our analysis of synthetic aromatic monoamine derivatives identified 7-fluorotryptamine as a more potent agonist of GPRC5A. These results highlight the utility of chemoproteomics to identify microbiota metabolite-interacting proteins and the development of small-molecule agonists for orphan receptors.
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Affiliation(s)
- Xiaohui Zhao
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Kathryn R Stein
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Victor Chen
- Laboratory of Chemical Biology and Microbial Pathogenesis, The Rockefeller University, New York City, NY, USA
| | - Matthew E Griffin
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA
| | - Luke L Lairson
- Department of Chemistry, Scripps Research, La Jolla, CA, USA
| | - Howard C Hang
- Department of Immunology and Microbiology, Scripps Research, La Jolla, CA, USA.
- Department of Chemistry, Scripps Research, La Jolla, CA, USA.
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48
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Mo K, Chu Y, Liu Y, Zheng G, Song K, Song Q, Zheng H, Tang Y, Tian X, Yao W, Fang H, Wang K, Jiang Y, Yang D, Chen Y, Huang C, Li T, Qu H, Song X, Zhou J. Targeting hnRNPC suppresses thyroid follicular epithelial cell apoptosis and necroptosis through m 6A-modified ATF4 in autoimmune thyroid disease. Pharmacol Res 2023; 196:106933. [PMID: 37729957 DOI: 10.1016/j.phrs.2023.106933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 09/16/2023] [Accepted: 09/17/2023] [Indexed: 09/22/2023]
Abstract
Both environmental and genetic factors contribute to the etiology of autoimmune thyroid disease (AITD) including Graves' disease (GD) and Hashimoto's thyroiditis (HT). However, the exact pathogenesis and interactions that occur between environmental factors and genes remain unclear, and therapeutic targets require further investigation due to limited therapeutic options. To solve such problems, this study utilized single-cell transcriptome, whole transcriptome, full-length transcriptome (Oxford nanopore technology), and metabolome sequencing to examine thyroid lesion tissues from 2 HT patients and 2 GD patients as well as healthy thyroid tissue from 1 control subject. HT patients had increased ATF4-positive thyroid follicular epithelial (ThyFoEp) cells, which significantly increased endoplasmic reticulum stress. The enhanced sustained stress resulted in cell death mainly including apoptosis and necroptosis. The ATF4-based global gene regulatory network and experimental validation revealed that N6-methyladenosine (m6A) reader hnRNPC promoted the transcriptional activity, synthesis, and translation of ATF4 through mediating m6A modification of ATF4. Increased ATF4 expression initiated endoplasmic reticulum stress signaling, which when sustained, caused apoptosis and necroptosis in ThyFoEp cells, and mediated HT development. Targeting hnRNPC and ATF4 notably decreased ThyFoEp cell death, thus ameliorating disease progression. Collectively, this study reveals the mechanisms by which microenvironmental cells in HT and GD patients trigger and amplify the thyroid autoimmune cascade response. Furthermore, we identify new therapeutic targets for the treatment of autoimmune thyroid disease, hoping to provide a potential way for targeted therapy.
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Affiliation(s)
- Ke Mo
- Key Laboratory of Spatiotemporal Single-Cell Technologies and Translational Medicine, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China; Experimental Center of BIOQGene, YuanDong International Academy of Life Sciences, 999077, Hong Kong, China
| | - Yongli Chu
- Department of Scientific Research, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China
| | - Yang Liu
- Department of Thyroid Surgery, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China
| | - Guibin Zheng
- Department of Thyroid Surgery, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China
| | - Kaiyu Song
- Department of Endocrinology, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China
| | - Qiong Song
- Key Laboratory of Spatiotemporal Single-Cell Technologies and Translational Medicine, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China; Experimental Center of BIOQGene, YuanDong International Academy of Life Sciences, 999077, Hong Kong, China
| | - Haitao Zheng
- Department of Thyroid Surgery, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China
| | - Yuxiao Tang
- Department of Endocrinology, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China
| | - Xinghan Tian
- Department of Critical Care Medicine, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China
| | - Wenjie Yao
- Department of Endocrinology, Binzhou Medical University, Yantai 264003, Shandong, China
| | - Han Fang
- Department of Otorhinolaryngology, Head and Neck Surgery, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China
| | - Kejian Wang
- Experimental Center of BIOQGene, YuanDong International Academy of Life Sciences, 999077, Hong Kong, China; Innovative Institute of Chinese Medicine and Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan 250300, Shandong, China
| | - Yongqiang Jiang
- Biology Institute, Guangxi Academy of Sciences, Nanning 530007, Guangxi, China
| | - Dengfeng Yang
- Biology Institute, Guangxi Academy of Sciences, Nanning 530007, Guangxi, China
| | - Yixuan Chen
- Experimental Center of BIOQGene, YuanDong International Academy of Life Sciences, 999077, Hong Kong, China; Biology Institute, Guangxi Academy of Sciences, Nanning 530007, Guangxi, China
| | - Chengyu Huang
- Experimental Center of BIOQGene, YuanDong International Academy of Life Sciences, 999077, Hong Kong, China; Biology Institute, Guangxi Academy of Sciences, Nanning 530007, Guangxi, China
| | - Ting Li
- Experimental Center of BIOQGene, YuanDong International Academy of Life Sciences, 999077, Hong Kong, China; Biology Institute, Guangxi Academy of Sciences, Nanning 530007, Guangxi, China
| | - Hongmei Qu
- Departments of Obstetrics and Gynecology, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China.
| | - Xicheng Song
- Key Laboratory of Spatiotemporal Single-Cell Technologies and Translational Medicine, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China; Department of Otorhinolaryngology, Head and Neck Surgery, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China.
| | - Jin Zhou
- Key Laboratory of Spatiotemporal Single-Cell Technologies and Translational Medicine, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China; Department of Endocrinology, Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, Shandong, China.
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49
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Lee AJ, Gangi LR, Zandkarimi F, Stockwell BR, Hung CT. Red blood cell exposure increases chondrocyte susceptibility to oxidative stress following hemarthrosis. Osteoarthritis Cartilage 2023; 31:1365-1376. [PMID: 37364817 PMCID: PMC10529126 DOI: 10.1016/j.joca.2023.06.007] [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: 12/13/2022] [Revised: 05/11/2023] [Accepted: 06/13/2023] [Indexed: 06/28/2023]
Abstract
OBJECTIVE The detrimental effects of blood exposure on articular tissues are well characterized, but the individual contributions of specific whole blood components are yet to be fully elucidated. Better understanding of mechanisms that drive cell and tissue damage in hemophilic arthropathy will inform novel therapeutic strategies. The studies here aimed to identify the specific contributions of intact and lysed red blood cells (RBCs) on cartilage and the therapeutic potential of Ferrostatin-1 in the context of lipid changes, oxidative stress, and ferroptosis. METHODS Changes to biochemical and mechanical properties following intact RBC treatment were assessed in human chondrocyte-based tissue-engineered cartilage constructs and validated against human cartilage explants. Chondrocyte monolayers were assayed for changes to intracellular lipid profiles and the presence of oxidative and ferroptotic mechanisms. RESULTS Markers of tissue breakdown were observed in cartilage constructs without parallel losses in DNA (control: 786.3 (102.2) ng/mg; RBCINT: 751 (126.4) ng/mg; P = 0.6279), implicating nonlethal chondrocyte responses to intact RBCs. Dose-dependent loss of viability in response to intact and lysed RBCs was observed in chondrocyte monolayers, with greater toxicity observed with lysates. Intact RBCs induced changes to chondrocyte lipid profiles, upregulating highly oxidizable fatty acids (e.g., FA 18:2) and matrix disrupting ceramides. RBC lysates induced cell death via oxidative mechanisms that resemble ferroptosis. CONCLUSIONS Intact RBCs induce intracellular phenotypic changes to chondrocytes that increase vulnerability to tissue damage while lysed RBCs have a more direct influence on chondrocyte death by mechanisms that are representative of ferroptosis.
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Affiliation(s)
- Andy J Lee
- Department of Biomedical Engineering, Columbia University, 351 Engineering Terrace, Mail Code 8904, 1210 Amsterdam Avenue, New York, NY, USA.
| | - Lianna R Gangi
- Department of Biomedical Engineering, Columbia University, 351 Engineering Terrace, Mail Code 8904, 1210 Amsterdam Avenue, New York, NY, USA.
| | - Fereshteh Zandkarimi
- Department of Chemistry, Columbia University, 216 Havemeyer Hall, 3000 Broadway, Mail Code 3183, New York, NY, USA.
| | - Brent R Stockwell
- Department of Chemistry, Columbia University, 216 Havemeyer Hall, 3000 Broadway, Mail Code 3183, New York, NY, USA; Department of Biological Sciences, Columbia University, 1208 NWC Building, 550 West 120th St. M.C. 4846, New York, NY, USA.
| | - Clark T Hung
- Department of Biomedical Engineering, Columbia University, 351 Engineering Terrace, Mail Code 8904, 1210 Amsterdam Avenue, New York, NY, USA; Department of Orthopaedic Surgery, Columbia University, New York, NY, USA.
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Bunyat-Zada AR, Ross AC. Highlights of bioinformatic tools and methods for validating bioinformatics derived hypotheses for microbial natural products research. Curr Opin Chem Biol 2023; 76:102367. [PMID: 37453164 DOI: 10.1016/j.cbpa.2023.102367] [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: 12/20/2022] [Revised: 06/14/2023] [Accepted: 06/16/2023] [Indexed: 07/18/2023]
Abstract
Historically, bacterial natural products have served as an excellent source of drug leads, however, in recent decades the rate of discovery has slowed due to multiple challenges. Rapid advances in genome sequencing science in recent years have revealed the vast untapped encoded potential of bacteria to make natural products. To access these molecules, researchers can employ the ever-growing array of bioinformatic tools at their disposal and leverage newly developed experimental approaches to validate these bioinformatic-driven hypotheses. When used together effectively, bioinformatic and experimental tools enable researchers to deeply examine the full diversity of bacterial natural products. This review briefly outlines recent bioinformatic tools that can facilitate natural product research in bacteria including the use of CRISPR, co-occurrence network analysis, and combinatorial generation of microbial natural products to test bioinformatic hypotheses in the lab.
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Affiliation(s)
- Amir R Bunyat-Zada
- Department of Chemistry, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Avena C Ross
- Department of Chemistry, Queen's University, Kingston, ON, K7L 3N6, Canada.
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