1
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Paiva AC, Teixeira CA, Hantao LW. Exploring accurate mass measurements in pixel-based chemometrics: Advancing coffee classification with GC-HRMS-A proof of concept study. J Chromatogr A 2024; 1731:465171. [PMID: 39059306 DOI: 10.1016/j.chroma.2024.465171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 07/04/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024]
Abstract
This paper presents a study that assesses the application of chemometrics for classifying coffee samples in a quality control context. High-resolution and accurate mass measurements were utilized as input for pixel-based orthogonal partial least squares discriminant analysis (OPLS-DA) models. The compositional data were acquired through a fully automated workflow combining headspace solid-phase microextraction and gas chromatography-high-resolution mass spectrometry (GC-HRMS) using an FT-Orbitrap® mass analyzer. A workflow centered on accurate mass measurements was successfully utilized for group-type analysis, offering an alternative to methods relying solely on MS similarity searches. The predictive models underwent thorough evaluation, demonstrating robust multivariate classification performance. Five key coffee attributes, bitterness, acidity, body, intensity, and roasting level were successfully predicted using GC-HRMS data. The results revealed strong predictive accuracy across all models, ranging from 88.9 % (bitterness) to 94.4 % (roasting level). This study represents a significant advancement in automating methods for coffee quality control, notably increasing the predictive ability of the models compared to existing literature.
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Affiliation(s)
- Andre Cunha Paiva
- Institute of Chemistry, University of Campinas, 270 Monteiro Lobato, Campinas, SP 13083-862, Brazil; National Institute of Science and Technology in Bioanalytics (INCTBio), SP, Campinas, 13083-862 Brazil
| | - Carlos Alberto Teixeira
- Institute of Chemistry, University of Campinas, 270 Monteiro Lobato, Campinas, SP 13083-862, Brazil; National Institute of Science and Technology in Bioanalytics (INCTBio), SP, Campinas, 13083-862 Brazil
| | - Leandro Wang Hantao
- Institute of Chemistry, University of Campinas, 270 Monteiro Lobato, Campinas, SP 13083-862, Brazil; National Institute of Science and Technology in Bioanalytics (INCTBio), SP, Campinas, 13083-862 Brazil.
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2
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Zhang Y, Zhao H, Zhao J, Lv W, Jia X, Lu X, Zhao X, Xu G. Quantified Metabolomics and Lipidomics Profiles Reveal Serum Metabolic Alterations and Distinguished Metabolites of Seven Chronic Metabolic Diseases. J Proteome Res 2024; 23:3076-3087. [PMID: 38407022 DOI: 10.1021/acs.jproteome.3c00760] [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] [Indexed: 02/27/2024]
Abstract
The co-occurrence of multiple chronic metabolic diseases is highly prevalent, posing a huge health threat. Clarifying the metabolic associations between them, as well as identifying metabolites which allow discrimination between diseases, will provide new biological insights into their co-occurrence. Herein, we utilized targeted serum metabolomics and lipidomics covering over 700 metabolites to characterize metabolic alterations and associations related to seven chronic metabolic diseases (obesity, hypertension, hyperuricemia, hyperglycemia, hypercholesterolemia, hypertriglyceridemia, fatty liver) from 1626 participants. We identified 454 metabolites were shared among at least two chronic metabolic diseases, accounting for 73.3% of all 619 significant metabolite-disease associations. We found amino acids, lactic acid, 2-hydroxybutyric acid, triacylglycerols (TGs), and diacylglycerols (DGs) showed connectivity across multiple chronic metabolic diseases. Many carnitines were specifically associated with hyperuricemia. The hypercholesterolemia group showed obvious lipid metabolism disorder. Using logistic regression models, we further identified distinguished metabolites of seven chronic metabolic diseases, which exhibited satisfactory area under curve (AUC) values ranging from 0.848 to 1 in discovery and validation sets. Overall, quantitative metabolome and lipidome data sets revealed widespread and interconnected metabolic disorders among seven chronic metabolic diseases. The distinguished metabolites are useful for diagnosing chronic metabolic diseases and provide a reference value for further clinical intervention and management based on metabolomics strategy.
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Affiliation(s)
- Yuqing Zhang
- School of Chemistry, Dalian University of Technology, Dalian 116024, P. R. China
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
| | - Hui Zhao
- Department of the Health Checkup Center, The Second Hospital of Dalian Medical University, Dalian 116023, P. R. China
| | - Jinhui Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Science, Beijing 100049, P. R. China
| | - Wangjie Lv
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Science, Beijing 100049, P. R. China
| | - Xueni Jia
- Department of the Health Checkup Center, The Second Hospital of Dalian Medical University, Dalian 116023, P. R. China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
| | - Guowang Xu
- School of Chemistry, Dalian University of Technology, Dalian 116024, P. R. China
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Science, Beijing 100049, P. R. China
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3
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Engström Ruud L, Font-Gironès F, Zajdel J, Kern L, Teixidor-Deulofeu J, Mannerås-Holm L, Carreras A, Becattini B, Björefeldt A, Hanse E, Fenselau H, Solinas G, Brüning JC, Wunderlich TF, Bäckhed F, Ruud J. Activation of GFRAL + neurons induces hypothermia and glucoregulatory responses associated with nausea and torpor. Cell Rep 2024; 43:113960. [PMID: 38507407 DOI: 10.1016/j.celrep.2024.113960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 01/11/2024] [Accepted: 02/28/2024] [Indexed: 03/22/2024] Open
Abstract
GFRAL-expressing neurons actuate aversion and nausea, are targets for obesity treatment, and may mediate metformin effects by long-term GDF15-GFRAL agonism. Whether GFRAL+ neurons acutely regulate glucose and energy homeostasis is, however, underexplored. Here, we report that cell-specific activation of GFRAL+ neurons using a variety of techniques causes a torpor-like state, including hypothermia, the release of stress hormones, a shift from glucose to lipid oxidation, and impaired insulin sensitivity, glucose tolerance, and skeletal muscle glucose uptake but augmented glucose uptake in visceral fat. Metabolomic analysis of blood and transcriptomics of muscle and fat indicate alterations in ketogenesis, insulin signaling, adipose tissue differentiation and mitogenesis, and energy fluxes. Our findings indicate that acute GFRAL+ neuron activation induces endocrine and gluco- and thermoregulatory responses associated with nausea and torpor. While chronic activation of GFRAL signaling promotes weight loss in obesity, these results show that acute activation of GFRAL+ neurons causes hypothermia and hyperglycemia.
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Affiliation(s)
- Linda Engström Ruud
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Ferran Font-Gironès
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Joanna Zajdel
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Lara Kern
- Max Planck Institute for Metabolism Research, Cologne, Germany
| | - Júlia Teixidor-Deulofeu
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Louise Mannerås-Holm
- Department of Molecular and Clinical Medicine, The Wallenberg Laboratory, Institute of Medicine, University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Alba Carreras
- Department of Molecular and Clinical Medicine, The Wallenberg Laboratory, Institute of Medicine, University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Barbara Becattini
- Department of Molecular and Clinical Medicine, The Wallenberg Laboratory, Institute of Medicine, University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Andreas Björefeldt
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Eric Hanse
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Giovanni Solinas
- Department of Molecular and Clinical Medicine, The Wallenberg Laboratory, Institute of Medicine, University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jens C Brüning
- Max Planck Institute for Metabolism Research, Cologne, Germany
| | | | - Fredrik Bäckhed
- Department of Molecular and Clinical Medicine, The Wallenberg Laboratory, Institute of Medicine, University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Johan Ruud
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
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4
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Lee SH, Lin WY, Cheng TJ. Microbiota-mediated metabolic perturbations in the gut and brain of mice after microplastic exposure. CHEMOSPHERE 2024; 350:141026. [PMID: 38145850 DOI: 10.1016/j.chemosphere.2023.141026] [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: 09/14/2023] [Revised: 12/20/2023] [Accepted: 12/21/2023] [Indexed: 12/27/2023]
Abstract
Microplastics (MPs), emerging environmental toxicants, have drawn attention because of their wide distribution in the environment. Exposure to MPs induces gut microbiota dysbiosis, intestinal barrier dysfunction, metabolic perturbations, and neurotoxicity in different rodents. However, the relationship between MPs, gut microbiota, and the metabolome of the gut and brain in mice remains unclear. In this study, female C57BL/6 mice were orally gavaged with vehicle, 200 nm MP, and 800 nm MP three times per week for four weeks. Cecal contents were collected for gut microbiota analysis using 16S rRNA gene sequencing. Intestinal and brain tissues from mice were used to determine metabolic profiles using liquid chromatography-mass spectrometry (LC-MS). The results showed that MP altered microbiota composition, accompanied by metabolic perturbations in the mouse gut and brain. Specifically, Firmicutes and Bacteroidetes were suggested to be important phyla for MP exposure, partially dominating further metabolite alterations. Simultaneously, MP-induced metabolic profiles were associated with energy homeostasis and bile acid, nucleotide, and carnitine metabolic pathways. The results of the mediation analysis further revealed an MP-microbiota-metabolite relationship. Our results indicate that MPs can induce gut dysbiosis and disturb metabolic dysfunction in the mouse brain and/or intestine. Integrative omics approaches have the potential to monitor MP-induced molecular responses in various organs and systematically elucidate the complex mechanisms of human health effects.
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Affiliation(s)
- Sheng-Han Lee
- School of Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan
| | - Wan-Yu Lin
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; Master of Public Health Degree Program, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Tsun-Jen Cheng
- Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan.
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5
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Queiroz KA, Vale EP, Martín-Pastor M, Sólon LGS, Sousa FFO. Metabolomic Profile, Plasmatic Levels of Losartan and EXP3174, Blood Pressure Control in Hypertensive Patients and Their Correlation with COVID-19. Pharmaceuticals (Basel) 2023; 16:1290. [PMID: 37765098 PMCID: PMC10535928 DOI: 10.3390/ph16091290] [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: 06/20/2023] [Revised: 07/21/2023] [Accepted: 07/27/2023] [Indexed: 09/29/2023] Open
Abstract
Systemic arterial hypertension (SAH) is one of the most prevalent chronic diseases worldwide and is related to serious health complications. It has been pointed out as a major risk factor for COVID-19. This study aimed to determine the impact of COVID-19 on the metabolomic profile, the correlation with the plasmatic levels of losartan and its active metabolite (EXP3174), biochemical markers, and blood pressure (BP) control in hypertensive patients. 1H NMR metabolomic profiles of hypertensive and normotensive patients with and without previous COVID-19 diagnosis were identified. Plasmatic levels of LOS and EXP3174 were correlated with BP, biochemical markers, and the metabolomic fingerprint of the groups. Biomarkers linked to important aspects of SAH and COVID-19 were identified, such as glucose, glutamine, arginine, creatinine, alanine, choline, erythritol, homogentisate, 0-tyrosine, and 2-hydroxybutyrate. Those metabolites are indicative of metabolic alterations, kidney damage, pulmonary dysfunction, and persistent inflammation, which can be found in both diseases. Some hypertensive patients did not reach the therapeutic levels of LOS and EXP3174, while the BP control was also limited among the normotensive patients with previous COVID-19 diagnoses. Metabolomics proved to be an important tool for assessing the effectiveness of losartan pharmacotherapy and the damage caused by SAH and COVID-19 in hypertensive patients.
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Affiliation(s)
- Kamila A. Queiroz
- Graduate Program on Pharmaceutical Sciences, Department of Biological & Health Sciences, Federal University of Amapa, Macapa 68903-419, Brazil; (K.A.Q.); (L.G.S.S.)
- Laboratory of Quality Control, Bromatology and Microbiology, Department of Biological & Health Sciences, Federal University of Amapa, Macapa 68903-419, Brazil;
| | - Everton P. Vale
- Laboratory of Quality Control, Bromatology and Microbiology, Department of Biological & Health Sciences, Federal University of Amapa, Macapa 68903-419, Brazil;
- Graduate Program on Pharmaceutical Innovation, Department of Biological & Health Sciences, Federal University of Amapa, Macapa 68903-419, Brazil
| | - Manuel Martín-Pastor
- Unidade de Resonancia Magnetica, Área de Infraestruturas de Investigación, Campus Vida, Universidad de Santiago de Compostela, 15782 Santiago de Compostela, Spain;
| | - Lílian G. S. Sólon
- Graduate Program on Pharmaceutical Sciences, Department of Biological & Health Sciences, Federal University of Amapa, Macapa 68903-419, Brazil; (K.A.Q.); (L.G.S.S.)
- Laboratory of Quality Control, Bromatology and Microbiology, Department of Biological & Health Sciences, Federal University of Amapa, Macapa 68903-419, Brazil;
| | - Francisco F. O. Sousa
- Graduate Program on Pharmaceutical Sciences, Department of Biological & Health Sciences, Federal University of Amapa, Macapa 68903-419, Brazil; (K.A.Q.); (L.G.S.S.)
- Laboratory of Quality Control, Bromatology and Microbiology, Department of Biological & Health Sciences, Federal University of Amapa, Macapa 68903-419, Brazil;
- Graduate Program on Pharmaceutical Innovation, Department of Biological & Health Sciences, Federal University of Amapa, Macapa 68903-419, Brazil
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6
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Simić K, Miladinović Z, Todorović N, Trifunović S, Avramović N, Gavrilović A, Jovanović S, Gođevac D, Vujisić L, Tešević V, Tasic L, Mandić B. Metabolomic Profiling of Bipolar Disorder by 1H-NMR in Serbian Patients. Metabolites 2023; 13:metabo13050607. [PMID: 37233648 DOI: 10.3390/metabo13050607] [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: 03/31/2023] [Revised: 04/21/2023] [Accepted: 04/25/2023] [Indexed: 05/27/2023] Open
Abstract
Bipolar disorder (BD) is a brain disorder that causes changes in a person's mood, energy, and ability to function. It has a prevalence of 60 million people worldwide, and it is among the top 20 diseases with the highest global burden. The complexity of this disease, including diverse genetic, environmental, and biochemical factors, and diagnoses based on the subjective recognition of symptoms without any clinical test of biomarker identification create significant difficulties in understanding and diagnosing BD. A 1H-NMR-based metabolomic study applying chemometrics of serum samples of Serbian patients with BD (33) and healthy controls (39) was explored, providing the identification of 22 metabolites for this disease. A biomarker set including threonine, aspartate, gamma-aminobutyric acid, 2-hydroxybutyric acid, serine, and mannose was established for the first time in BD serum samples by an NMR-based metabolomics study. Six identified metabolites (3-hydroxybutyric acid, arginine, lysine, tyrosine, phenylalanine, and glycerol) are in agreement with the previously determined NMR-based sets of serum biomarkers in Brazilian and/or Chinese patient samples. The same established metabolites (lactate, alanine, valine, leucine, isoleucine, glutamine, glutamate, glucose, and choline) in three different ethnic and geographic origins (Serbia, Brazil, and China) might have a crucial role in the realization of a universal set of NMR biomarkers for BD.
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Affiliation(s)
- Katarina Simić
- Institute of Chemistry, Technology and Metallurgy, National Institute, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia
| | - Zoran Miladinović
- Institute of General and Physical Chemistry, Studentski trg 12-16, 11158 Belgrade, Serbia
| | - Nina Todorović
- Institute of Chemistry, Technology and Metallurgy, National Institute, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia
| | - Snežana Trifunović
- University of Belgrade - Faculty of Chemistry, Studentski trg 12-16, 11000 Belgrade, Serbia
| | - Nataša Avramović
- University of Belgrade - Faculty of Medicine, Institute of Medical Chemistry, Višegradska 26, 11000 Belgrade, Serbia
| | - Aleksandra Gavrilović
- Special Hospital for Psychiatric Diseases "Kovin", Cara Lazara 253, 26220 Kovin, Serbia
| | - Silvana Jovanović
- Special Hospital for Psychiatric Diseases "Kovin", Cara Lazara 253, 26220 Kovin, Serbia
| | - Dejan Gođevac
- Institute of Chemistry, Technology and Metallurgy, National Institute, University of Belgrade, Studentski trg 12-16, 11000 Belgrade, Serbia
| | - Ljubodrag Vujisić
- University of Belgrade - Faculty of Chemistry, Studentski trg 12-16, 11000 Belgrade, Serbia
| | - Vele Tešević
- University of Belgrade - Faculty of Chemistry, Studentski trg 12-16, 11000 Belgrade, Serbia
| | - Ljubica Tasic
- Institute of Chemistry, Organic Chemistry Department, State University of Campinas, Campinas 13083-970, SP, Brazil
| | - Boris Mandić
- University of Belgrade - Faculty of Chemistry, Studentski trg 12-16, 11000 Belgrade, Serbia
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7
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Dai X, Bai R, Xie B, Xiang J, Miao X, Shi Y, Yu F, Cong B, Wen D, Ma C. A Metabolomics-Based Study on the Discriminative Classification Models and Toxicological Mechanism of Estazolam Fatal Intoxication. Metabolites 2023; 13:metabo13040567. [PMID: 37110225 PMCID: PMC10144813 DOI: 10.3390/metabo13040567] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/07/2023] [Accepted: 04/12/2023] [Indexed: 04/29/2023] Open
Abstract
Fatal intoxication with sedative-hypnotic drugs is increasing yearly. However, the plasma drug concentration data for fatal intoxication involving these substances are not systematic and even overlap with the intoxication group. Therefore, developing a more precise and trustworthy approach to determining the cause of death is necessary. This study analyzed mice plasma and brainstem samples using the liquid chromatography-high resolution tandem mass spectrometry (LC-HR MS/MS)-based metabolomics method to create discriminative classification models for estazolam fatal intoxication (EFI). The most perturbed metabolic pathway between the EFI and EIND (estazolam intoxication non-death) was examined, Both EIND and EFI groups were administered 500 mg of estazolam per 100 g of body weight. Mice that did not die beyond 8 hours were treated with cervical dislocation and were classified into the EIND groups; the lysine degradation pathway was verified by qPCR (Quantitative Polymerase Chain Reaction), metabolite quantitative and TEM (transmission electron microscopy) analysis. Non-targeted metabolomics analysis with EFI were the experimental group and four hypoxia-related non-drug-related deaths (NDRDs) were the control group. Mass spectrometry data were analyzed with Compound Discoverer (CD) 3.1 software and multivariate statistical analyses were performed using the online software MetaboAnalyst 5.0. After a series of analyses, the results showed the discriminative classification model in plasma was composed of three endogenous metabolites: phenylacetylglycine, creatine and indole-3-lactic acid, and in the brainstem was composed of palmitic acid, creatine, and indole-3-lactic acid. The specificity validation results showed that both classification models distinguished between the other four sedatives-hypnotics, with an area under ROC curve (AUC) of 0.991, and the classification models had an extremely high specificity. When comparing different doses of estazolam, the AUC value of each group was larger than 0.80, and the sensitivity was also high. Moreover, the stability results showed that the AUC value was equal to or very close to 1 in plasma samples stored at 4 °C for 0, 1, 5, 10 and 15 days; the predictive power of the classification model was stable within 15 days. The results of lysine degradation pathway validation revealed that the EFI group had the highest lysine and saccharopine concentrations (mean (ng/mg) = 1.089 and 1.2526, respectively) when compared to the EIND and control group, while the relative expression of SDH (saccharopine dehydrogenase) showed significantly lower in the EFI group (mean = 1.206). Both of these results were statistically significant. Furthermore, TEM analysis showed that the EFI group had the more severely damaged mitochondria. This work gives fresh insights into the toxicological processes of estazolam and a new method for identifying EFI-related causes of mortality.
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Affiliation(s)
- Xiaohui Dai
- Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China
- Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang 050017, China
| | - Rui Bai
- Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China
- Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang 050017, China
| | - Bing Xie
- Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China
- Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang 050017, China
| | - Jiahong Xiang
- Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China
- Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang 050017, China
| | - Xingang Miao
- Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China
- Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang 050017, China
- Forensic Science Centre of WATSON, Guangzhou 510440, China
| | - Yan Shi
- Shanghai Key Laboratory Medicine, Department of Forensic Toxicology, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China
| | - Feng Yu
- Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China
- Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang 050017, China
| | - Bin Cong
- Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China
- Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang 050017, China
| | - Di Wen
- Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China
- Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang 050017, China
| | - Chunling Ma
- Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang 050017, China
- Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang 050017, China
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8
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Sorochan Armstrong MD, Hinrich JL, de la Mata AP, Harynuk JJ. PARAFAC2×N: Coupled decomposition of multi-modal data with drift in N modes. Anal Chim Acta 2023; 1249:340909. [PMID: 36868765 DOI: 10.1016/j.aca.2023.340909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 01/23/2023] [Accepted: 01/30/2023] [Indexed: 02/04/2023]
Abstract
Analysis of GC×GC-TOFMS data for large numbers of poorly-resolved peaks, and for large numbers of samples remains an enduring problem that hinders the widespread application of the technique. For multiple samples, GC×GC-TOFMS data for specific chromatographic regions manifests as a 4th order tensor of I mass spectral acquisitions, J mass channels, K modulations, and L samples. Chromatographic drift is common along both the first-dimension (modulations), and along the second-dimension (mass spectral acquisitions), while drift along the mass channel is for all practical purposes nonexistent. A number of solutions to handling GC×GC-TOFMS data have been proposed: these involve reshaping the data to make it amenable to either 2nd order decomposition techniques based on Multivariate Curve Resolution (MCR), or 3rd order decomposition techniques such as Parallel Factor Analysis 2 (PARAFAC2). PARAFAC2 has been utilised to model chromatographic drift along one mode, which has enabled its use for robust decomposition of multiple GC-MS experiments. Although extensible, it is not straightforward to implement a PARAFAC2 model that accounts for drift along multiple modes. In this submission, we demonstrate a new approach and a general theory for modelling data with drift along multiple modes, for applications in multidimensional chromatography with multivariate detection. The proposed model captures over 99.9% of variance for a synthetic data set, presenting an extreme example of peak drift and co-elution across two modes of separation.
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Affiliation(s)
| | - Jesper Løve Hinrich
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, Copenhagen, DK-1958, Denmark
| | - A Paulina de la Mata
- Department of Chemistry, University of Alberta, 11227 Saskatchewan Dr NW, Edmonton, T6G 2G2, Alberta, Canada
| | - James J Harynuk
- Department of Chemistry, University of Alberta, 11227 Saskatchewan Dr NW, Edmonton, T6G 2G2, Alberta, Canada.
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9
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Okut H, Lu Y, Palmer ND, Chen YDI, Taylor KD, Norris JM, Lorenzo C, Rotter JI, Langefeld CD, Wagenknecht LE, Bowden DW, Ng MCY. Metabolomic profiling of glucose homeostasis in African Americans: the Insulin Resistance Atherosclerosis Family Study (IRAS-FS). Metabolomics 2023; 19:35. [PMID: 37005925 PMCID: PMC10068644 DOI: 10.1007/s11306-023-01984-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 03/04/2023] [Indexed: 04/04/2023]
Abstract
INTRODUCTION African Americans are at increased risk for type 2 diabetes. OBJECTIVES This work aimed to examine metabolomic signature of glucose homeostasis in African Americans. METHODS We used an untargeted liquid chromatography-mass spectrometry metabolomic approach to comprehensively profile 727 plasma metabolites among 571 African Americans from the Insulin Resistance Atherosclerosis Family Study (IRAS-FS) and investigate the associations between these metabolites and both the dynamic (SI, insulin sensitivity; AIR, acute insulin response; DI, disposition index; and SG, glucose effectiveness) and basal (HOMA-IR and HOMA-B) measures of glucose homeostasis using univariate and regularized regression models. We also compared the results with our previous findings in the IRAS-FS Mexican Americans. RESULTS We confirmed increased plasma metabolite levels of branched-chain amino acids and their metabolic derivatives, 2-aminoadipate, 2-hydroxybutyrate, glutamate, arginine and its metabolic derivatives, carbohydrate metabolites, and medium- and long-chain fatty acids were associated with insulin resistance, while increased plasma metabolite levels in the glycine, serine and threonine metabolic pathway were associated with insulin sensitivity. We also observed a differential ancestral effect of glutamate on glucose homeostasis with significantly stronger effects observed in African Americans than those previously observed in Mexican Americans. CONCLUSION We extended the observations that metabolites are useful biomarkers in the identification of prediabetes in individuals at risk of type 2 diabetes in African Americans. We revealed, for the first time, differential ancestral effect of certain metabolites (i.e., glutamate) on glucose homeostasis traits. Our study highlights the need for additional comprehensive metabolomic studies in well-characterized multiethnic cohorts.
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Affiliation(s)
- Hayrettin Okut
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Population Health, University of Kansas School of Medicine-Wichita, Wichita, KS, USA
| | - Yingchang Lu
- Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Nicholette D Palmer
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yii-Der Ida Chen
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jill M Norris
- Departments of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA
| | - Carlos Lorenzo
- Department of Medicine, University of Texas Health Science Center, San Antonio, TX, USA
| | - Jerome I Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Donald W Bowden
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Maggie C Y Ng
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
- Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
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10
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Mistry S, Riches NO, Gouripeddi R, Facelli JC. Environmental exposures in machine learning and data mining approaches to diabetes etiology: A scoping review. Artif Intell Med 2023; 135:102461. [PMID: 36628796 PMCID: PMC9834645 DOI: 10.1016/j.artmed.2022.102461] [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: 04/05/2022] [Revised: 10/06/2022] [Accepted: 11/23/2022] [Indexed: 12/03/2022]
Abstract
BACKGROUND Environmental exposures are implicated in diabetes etiology, but are poorly understood due to disease heterogeneity, complexity of exposures, and analytical challenges. Machine learning and data mining are artificial intelligence methods that can address these limitations. Despite their increasing adoption in etiology and prediction of diabetes research, the types of methods and exposures analyzed have not been thoroughly reviewed. OBJECTIVE We aimed to review articles that implemented machine learning and data mining methods to understand environmental exposures in diabetes etiology and disease prediction. METHODS We queried PubMed and Scopus databases for machine learning and data mining studies that used environmental exposures to understand diabetes etiology on September 19th, 2022. Exposures were classified into specific external, general external, or internal exposures. We reviewed machine learning and data mining methods and characterized the scope of environmental exposures studied in the etiology of general diabetes, type 1 diabetes, type 2 diabetes, and other types of diabetes. RESULTS We identified 44 articles for inclusion. Specific external exposures were the most common exposures studied, and supervised models were the most common methods used. Well-established specific external exposures of low physical activity, high cholesterol, and high triglycerides were predictive of general diabetes, type 2 diabetes, and prediabetes, while novel metabolic and gut microbiome biomarkers were implicated in type 1 diabetes. DISCUSSION The use of machine learning and data mining methods to elucidate environmental triggers of diabetes was largely limited to well-established risk factors identified using easily explainable and interpretable models. Future studies should seek to leverage machine learning and data mining to explore the temporality and co-occurrence of multiple exposures and further evaluate the role of general external and internal exposures in diabetes etiology.
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Affiliation(s)
- Sejal Mistry
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA; Center of Excellence for Exposure Health Informatics, University of Utah, Salt Lake City, UT, USA
| | - Naomi O Riches
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA; Center of Excellence for Exposure Health Informatics, University of Utah, Salt Lake City, UT, USA; Department of Obstetrics and Gynecology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Ramkiran Gouripeddi
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA; Center of Excellence for Exposure Health Informatics, University of Utah, Salt Lake City, UT, USA; Clinical and Translational Science Institute, University of Utah, Salt Lake City, UT, USA
| | - Julio C Facelli
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA; Center of Excellence for Exposure Health Informatics, University of Utah, Salt Lake City, UT, USA; Clinical and Translational Science Institute, University of Utah, Salt Lake City, UT, USA.
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11
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Yamazaki K, Miyauchi E, Kato T, Sato K, Suda W, Tsuzuno T, Yamada-Hara M, Sasaki N, Ohno H, Yamazaki K. Dysbiotic human oral microbiota alters systemic metabolism via modulation of gut microbiota in germ-free mice. J Oral Microbiol 2022; 14:2110194. [PMID: 35966937 PMCID: PMC9373767 DOI: 10.1080/20002297.2022.2110194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Background The effect of oral microbiota on the intestinal microbiota has garnered growing attention as a mechanism linking periodontal diseases to systemic diseases. However, the salivary microbiota is diverse and comprises numerous bacteria with a largely similar composition in healthy individuals and periodontitis patients. Aim We explored how health-associated and periodontitis-associated salivary microbiota differently colonized the intestine and their subsequent systemic effects. Methods The salivary microbiota was collected from a healthy individual and a periodontitis patient and gavaged into C57BL/6NJcl[GF] mice. Gut microbial communities, hepatic gene expression profiles, and serum metabolites were analyzed. Results The gut microbial composition was significantly different between periodontitis-associated microbiota-administered (PAO) and health-associated oral microbiota-administered (HAO) mice. The hepatic gene expression profile demonstrated a distinct pattern between the two groups, with higher expression of lipid and glucose metabolism-related genes. Disease-associated metabolites such as 2-hydroxyisobutyric acid and hydroxybenzoic acid were elevated in PAO mice. These metabolites were significantly correlated with characteristic gut microbial taxa in PAO mice. Conversely, health-associated oral microbiota were associated with higher levels of beneficial serum metabolites in HAO mice. Conclusion The multi-omics approach used in this study revealed that periodontitis-associated oral microbiota is associated with the induction of disease phenotype when they colonized the gut of germ-free mice.
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Affiliation(s)
- Kyoko Yamazaki
- Division of Periodontology, Niigata University Graduate School of Medical and Dental Sciences, Niigata Japan
| | - Eiji Miyauchi
- Laboratory for Intestinal Ecosystem, RIKEN Centre for Integrative Medical Sciences (IMS), Kanagawa Japan
- Laboratory of Mucosal Ecosystem Design, Institute for Molecular and Cellular Regulation, Gunma University, Maebashi, Gunma Japan
| | - Tamotsu Kato
- Laboratory for Intestinal Ecosystem, RIKEN Centre for Integrative Medical Sciences (IMS), Kanagawa Japan
- Immunobiology Laboratory, Graduate School of Medical Life Science, Yokohama City University, Kanagawa Japan
| | - Keisuke Sato
- Division of Periodontology, Niigata University Graduate School of Medical and Dental Sciences, Niigata Japan
| | - Wataru Suda
- Laboratory for Microbiome Sciences, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Takahiro Tsuzuno
- Division of Periodontology, Niigata University Graduate School of Medical and Dental Sciences, Niigata Japan
| | - Miki Yamada-Hara
- Division of Periodontology, Niigata University Graduate School of Medical and Dental Sciences, Niigata Japan
| | - Nobuo Sasaki
- Laboratory of Mucosal Ecosystem Design, Institute for Molecular and Cellular Regulation, Gunma University, Maebashi, Gunma Japan
| | - Hiroshi Ohno
- Laboratory for Intestinal Ecosystem, RIKEN Centre for Integrative Medical Sciences (IMS), Kanagawa Japan
- Immunobiology Laboratory, Graduate School of Medical Life Science, Yokohama City University, Kanagawa Japan
- Laboratory for Microbiome Sciences, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kazuhisa Yamazaki
- Laboratory for Intestinal Ecosystem, RIKEN Centre for Integrative Medical Sciences (IMS), Kanagawa Japan
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12
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Handakas E, Chang K, Khandpur N, Vamos EP, Millett C, Sassi F, Vineis P, Robinson O. Metabolic profiles of ultra-processed food consumption and their role in obesity risk in British children. Clin Nutr 2022; 41:2537-2548. [PMID: 36223715 DOI: 10.1016/j.clnu.2022.09.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/11/2022] [Accepted: 09/05/2022] [Indexed: 12/27/2022]
Abstract
BACKGROUND & AIMS Higher consumption of ultra-processed foods (UPF) has been associated with childhood obesity, but underlying mechanisms remain unclear. We investigated plasma nuclear magnetic resonance metabolic profiles of higher UPF consumption and their role in obesity risk in the British ALSPAC cohort. METHODS We performed cross-sectional and prospective metabolome wide association analyses of UPF, calculated from food diaries using the NOVA classification. In cross-sectional analysis, we tested the association between UPF consumption and metabolic profile at 7 years (N = 4528), and in the prospective analysis we tested the association between UPF consumption at 13 years and metabolic profile at 17 years (N = 3086). Effects of UPF-associated metabolites at 7 years on subsequent fat mass accumulation were assessed using growth curve models. RESULTS At 7 years, UPF was associated with 115 metabolic traits including lower levels of branched-chain and aromatic amino acids and higher levels of citrate, glutamine, and monounsaturated fatty acids, which were also associated with greater fat mass accumulation. Reported intake of nutrients mediated associations with most metabolites, except for citrate. CONCLUSIONS UPF consumption among British children is associated with perturbation of multiple metabolic traits, many of which contribute to child obesity risk.
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Affiliation(s)
- Evangelos Handakas
- Μedical Research Council Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, United Kingdom
| | - Kiara Chang
- Public Health Policy Evaluation Unit, Imperial College London, London W6 8RP, United Kingdom
| | - Neha Khandpur
- Department of Nutrition, School of Public Health, University of São Paulo, São Paulo 01246-904, Brazil; Center for Epidemiological Research in Nutrition and Health, School of Public Health, University of São Paulo, São Paulo 01246-904, Brazil; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, U. S. A
| | - Eszter P Vamos
- Public Health Policy Evaluation Unit, Imperial College London, London W6 8RP, United Kingdom
| | - Christopher Millett
- Public Health Policy Evaluation Unit, Imperial College London, London W6 8RP, United Kingdom; Comprehensive Health Research Center and Public Health Research Centre, National School of Public Health, NOVA University Lisbon, Portugal
| | - Franco Sassi
- Centre for Health Economics & Policy Innovation, Department of Economics & Public Policy, Imperial College Business School, South Kensington Campus, London, United Kingdom
| | - Paolo Vineis
- Μedical Research Council Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, United Kingdom
| | - Oliver Robinson
- Μedical Research Council Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, United Kingdom; Mohn Centre for Children's Health and Well-being, School of Public Health, Imperial College London, United Kingdom.
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Lucio-Gutiérrez JR, Cordero-Pérez P, Farías-Navarro IC, Tijerina-Marquez R, Sánchez-Martínez C, Ávila-Velázquez JL, García-Hernández PA, Náñez-Terreros H, Coello-Bonilla J, Pérez-Trujillo M, Parella T, Torres-González L, Waksman-Minsky NH, Saucedo AL. Using nuclear magnetic resonance urine metabolomics to develop a prediction model of early stages of renal disease in subjects with type 2 diabetes. J Pharm Biomed Anal 2022; 219:114885. [DOI: 10.1016/j.jpba.2022.114885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 06/01/2022] [Accepted: 06/08/2022] [Indexed: 12/01/2022]
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Jiang C, Pan X, Luo J, Liu X, Zhang L, Liu Y, Lei G, Hu G, Li J. Alterations in Microbiota and Metabolites Related to Spontaneous Diabetes and Pre-Diabetes in Rhesus Macaques. Genes (Basel) 2022; 13:genes13091513. [PMID: 36140683 PMCID: PMC9498908 DOI: 10.3390/genes13091513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 08/22/2022] [Accepted: 08/22/2022] [Indexed: 11/25/2022] Open
Abstract
Spontaneous type 2 diabetes mellitus (T2DM) macaques are valuable resources for our understanding the pathological mechanism of T2DM. Based on one month’s fasting blood glucose survey, we identified seven spontaneous T2DM macaques and five impaired glucose regulation (IGR) macaques from 1408 captive individuals. FPG, HbA1c, FPI and IR values were significant higher in T2DM and IGR than in controls. 16S rRNA sequencing of fecal microbes showed the significantly greater abundance of Oribacterium, bacteria inhibiting the production of secondary bile acids, and Phascolarctobacterium, bacteria producing short-chain fatty acids was significantly lower in T2DM macaques. In addition, several opportunistic pathogens, such as Mogibacterium and Kocuria were significantly more abundant in both T2DM and IGR macaques. Fecal metabolites analysis based on UHPLC-MS identified 50 differential metabolites (DMs) between T2DM and controls, and 26 DMs between IGR and controls. The DMs were significantly enriched in the bile acids metabolism, fatty acids metabolism and amino acids metabolism pathways. Combining results from physiochemical parameters, microbiota and metabolomics, we demonstrate that the imbalance of gut microbial community leading to the dysfunction of glucose, bile acids, fatty acids and amino acids metabolism may contribute to the hyperglycaemia in macaques, and suggest several microbes and metabolites are potential biomarkers for T2DM and IGR macaques.
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Affiliation(s)
- Cong Jiang
- Key Laboratory of Bio-Resources and Eco-Environment (Ministry of Education), College of Life Sciences, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
| | - Xuan Pan
- Key Laboratory of Bio-Resources and Eco-Environment (Ministry of Education), College of Life Sciences, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
| | - Jinxia Luo
- Key Laboratory of Bio-Resources and Eco-Environment (Ministry of Education), College of Life Sciences, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
| | - Xu Liu
- Key Laboratory of Bio-Resources and Eco-Environment (Ministry of Education), College of Life Sciences, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
| | - Lin Zhang
- Key Laboratory of Bio-Resources and Eco-Environment (Ministry of Education), College of Life Sciences, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
| | - Yun Liu
- Key Laboratory of Bio-Resources and Eco-Environment (Ministry of Education), College of Life Sciences, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
| | - Guanglun Lei
- SCU-SGHB Joint Laboratory on Non-Human Primates Research, Sichuan Green-House Biotech Co., Ltd., Meishan 620000, China
| | - Gang Hu
- SCU-SGHB Joint Laboratory on Non-Human Primates Research, Sichuan Green-House Biotech Co., Ltd., Meishan 620000, China
| | - Jing Li
- Key Laboratory of Bio-Resources and Eco-Environment (Ministry of Education), College of Life Sciences, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
- Correspondence:
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NMR Metabolomics in Serum Fingerprinting of Schizophrenia Patients in a Serbian Cohort. Metabolites 2022; 12:metabo12080707. [PMID: 36005580 PMCID: PMC9416612 DOI: 10.3390/metabo12080707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 07/19/2022] [Accepted: 07/26/2022] [Indexed: 02/04/2023] Open
Abstract
Schizophrenia is a widespread mental disorder that leads to significant functional impairments and premature death. The state of the art indicates gaps in the understanding and diagnosis of this disease, but also the need for personalized and precise approaches to patients through customized medical treatment and reliable monitoring of treatment response. In order to fulfill existing gaps, the establishment of a universal set of disorder biomarkers is a necessary step. Metabolomic investigations of serum samples of Serbian patients with schizophrenia (51) and healthy controls (39), based on NMR analyses associated with chemometrics, led to the identification of 26 metabolites/biomarkers for this disorder. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models with prediction accuracies of 0.9718 and higher were accomplished during chemometric analysis. The established biomarker set includes aspartate/aspartic acid, lysine, 2-hydroxybutyric acid, and acylglycerols, which are identified for the first time in schizophrenia serum samples by NMR experiments. The other 22 identified metabolites in the Serbian samples are in accordance with the previously established NMR-based serum biomarker sets of Brazilian and/or Chinese patient samples. Thirteen metabolites (lactate/lactic acid, threonine, leucine, isoleucine, valine, glutamine, asparagine, alanine, gamma-aminobutyric acid, choline, glucose, glycine and tyrosine) that are common for three different ethnic and geographic origins (Serbia, Brazil and China) could be a good start point for the setup of a universal NMR serum biomarker set for schizophrenia.
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Chen Y, Li EM, Xu LY. Guide to Metabolomics Analysis: A Bioinformatics Workflow. Metabolites 2022; 12:357. [PMID: 35448542 PMCID: PMC9032224 DOI: 10.3390/metabo12040357] [Citation(s) in RCA: 58] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 04/12/2022] [Accepted: 04/14/2022] [Indexed: 02/05/2023] Open
Abstract
Metabolomics is an emerging field that quantifies numerous metabolites systematically. The key purpose of metabolomics is to identify the metabolites corresponding to each biological phenotype, and then provide an analysis of the mechanisms involved. Although metabolomics is important to understand the involved biological phenomena, the approach's ability to obtain an exhaustive description of the processes is limited. Thus, an analysis-integrated metabolomics, transcriptomics, proteomics, and other omics approach is recommended. Such integration of different omics data requires specialized statistical and bioinformatics software. This review focuses on the steps involved in metabolomics research and summarizes several main tools for metabolomics analyses. We also outline the most abnormal metabolic pathways in several cancers and diseases, and discuss the importance of multi-omics integration algorithms. Overall, our goal is to summarize the current metabolomics analysis workflow and its main analysis software to provide useful insights for researchers to establish a preferable pipeline of metabolomics or multi-omics analysis.
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Affiliation(s)
- Yang Chen
- The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, China
- Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, China
| | - En-Min Li
- The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, China
- Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou 515041, China
| | - Li-Yan Xu
- The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041,
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Rodríguez-García M, Fernández-Varo G, Hidalgo S, Rodríguez G, Martínez I, Zeng M, Casals E, Morales-Ruiz M, Casals G. Validation of a Microwave-Assisted Derivatization Gas Chromatography-Mass Spectrometry Method for the Quantification of 2-Hydroxybutyrate in Human Serum as an Early Marker of Diabetes Mellitus. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27061889. [PMID: 35335253 PMCID: PMC8950062 DOI: 10.3390/molecules27061889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 02/28/2022] [Accepted: 03/05/2022] [Indexed: 12/03/2022]
Abstract
Circulating levels of 2-hydroxybutyrate (2HB) are highly related to glycemic status in different metabolomic studies. According to recent evidence, 2HB is an early biomarker of the future development of dysglycemia and type 2 diabetes mellitus and may be causally related to the progression of normal subjects to impaired fasting glucose or insulin resistance. In the present study, we developed and validated a simple, specific and sensitive gas chromatography-mass spectrometry (GC-MS) method specifically intended to quantify serum levels of 2HB. Liquid–liquid extraction with ethyl acetate was followed by 2 min of microwave-assisted derivatization. The method presented acceptable accuracy, precision and recovery, and the limit of quantification was 5 µM. Levels of 2HB were found to be stable in serum after three freeze-thaw cycles, and at ambient temperature and at a temperature of 4 °C for up to 24 h. Extracts derivatized under microwave irradiation were stable for up to 96 h. No differences were found in 2HB concentrations measured in serum or plasma EDTA samples. In summary, the method is useful for a rapid, precise and accurate quantification of 2HB in serum samples assessed for the evaluation of dysglycemia and diabetes mellitus.
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Affiliation(s)
- María Rodríguez-García
- Service of Biochemistry and Molecular Genetics, Hospital Clinic Universitari, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain; (M.R.-G.); (G.F.-V.); (S.H.); (G.R.); (I.M.); (M.M.-R.)
| | - Guillermo Fernández-Varo
- Service of Biochemistry and Molecular Genetics, Hospital Clinic Universitari, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain; (M.R.-G.); (G.F.-V.); (S.H.); (G.R.); (I.M.); (M.M.-R.)
- Department of Biomedicine, University of Barcelona, 08905 Barcelona, Spain
| | - Susana Hidalgo
- Service of Biochemistry and Molecular Genetics, Hospital Clinic Universitari, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain; (M.R.-G.); (G.F.-V.); (S.H.); (G.R.); (I.M.); (M.M.-R.)
| | - Gabriela Rodríguez
- Service of Biochemistry and Molecular Genetics, Hospital Clinic Universitari, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain; (M.R.-G.); (G.F.-V.); (S.H.); (G.R.); (I.M.); (M.M.-R.)
| | - Irene Martínez
- Service of Biochemistry and Molecular Genetics, Hospital Clinic Universitari, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain; (M.R.-G.); (G.F.-V.); (S.H.); (G.R.); (I.M.); (M.M.-R.)
| | - Muling Zeng
- School of Biotechnology and Health Sciences, Wuyi University, Jiangmen 529020, China;
| | - Eudald Casals
- School of Biotechnology and Health Sciences, Wuyi University, Jiangmen 529020, China;
- Correspondence: (E.C.); (G.C.); Tel.: +34-93-227-5400-2667 (G.C.)
| | - Manuel Morales-Ruiz
- Service of Biochemistry and Molecular Genetics, Hospital Clinic Universitari, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain; (M.R.-G.); (G.F.-V.); (S.H.); (G.R.); (I.M.); (M.M.-R.)
- Department of Biomedicine, University of Barcelona, 08905 Barcelona, Spain
- Commission for the Biochemical Assessment of Hepatic Disease-SEQCML, 08036 Barcelona, Spain
| | - Gregori Casals
- Service of Biochemistry and Molecular Genetics, Hospital Clinic Universitari, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain; (M.R.-G.); (G.F.-V.); (S.H.); (G.R.); (I.M.); (M.M.-R.)
- Commission for the Biochemical Assessment of Hepatic Disease-SEQCML, 08036 Barcelona, Spain
- Correspondence: (E.C.); (G.C.); Tel.: +34-93-227-5400-2667 (G.C.)
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Li KP, Yuan M, Wu YL, Pineda M, Zhang CM, Chen YF, Chen ZQ, Rong XL, Turnbull JE, Guo J. A high-fat High-fructose Diet Dysregulates the Homeostatic Crosstalk Between Gut Microbiome, Metabolome and Immunity in an Experimental Model of Obesity. Mol Nutr Food Res 2022; 66:e2100950. [PMID: 35072983 DOI: 10.1002/mnfr.202100950] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 12/30/2021] [Indexed: 11/07/2022]
Abstract
SCOPE Ample evidence supports the prominent role of gut-liver axis in perpetuating pathological networks of high-fat high-fructose (HFF) diet induced metabolic disorders, however, the molecular mechanisms are still not fully understood. Herein, we aim to present a holistic delineation and scientific explanation for the crosstalk between the gut and liver, including the potential mediators involved in orchestrating the metabolic and immune systems. METHODS An experimental obesity associated metaflammation rat model was induced with a HFF diet. An integrative multi-omics analysis was then performed. Following the clues illustrated by the multi-omics discoveries, putative pathways were subsequently validated by RT-qPCR and Western blotting. RESULTS HFF diet led to obese phenotypes in rats, as well as histopathological changes. Integrated omics analysis showed there existed a strong interdependence among gut microbiota composition, intestinal metabolites and innate immunity regulation in the liver. Some carboxylic acids might contribute to gut-liver communication. Moreover, activation of the hepatic LPS-TLR4 pathway in obesity was confirmed. CONCLUSIONS HFF-intake disturbs gut flora homeostasis. Crosstalk between gut microbiota and innate immune system mediated hepatic metaflammation in obese rats, associated with LPS-TLR4 signaling pathway activation. Moreover, α-hydroxyisobutyric acid and some other organic acids may play a role as messengers in the liver-gut axis. High-fat high-fructose diet (HFF) induces obesity associated chronic inflammation; HFF dysregulates the rat intestinal metabolome and gut microbiota composition; HFF impacts hepatic expression of genes involved in innate immunity; Modulation of gut microbiota composition and innate immunity are connected partly via TLR4 signalling; Small molecular carboxylic acids are potential mediators of gut-liver axis communication in chronic obesity. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Kun-Ping Li
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
- Key Laboratory of Glycolipid Metabolic Diseases, Ministry of Education, Guangzhou, 510006, China
| | - Min Yuan
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
- Key Laboratory of Glycolipid Metabolic Diseases, Ministry of Education, Guangzhou, 510006, China
| | - Yong-Lin Wu
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
- Key Laboratory of Glycolipid Metabolic Diseases, Ministry of Education, Guangzhou, 510006, China
| | - Miguel Pineda
- Institute of infection, immunity & inflammation, University of Glasgow, University Place, Glasgow, G12 8TA, UK
| | - Chu-Mei Zhang
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
- Key Laboratory of Glycolipid Metabolic Diseases, Ministry of Education, Guangzhou, 510006, China
| | - Yan-Fen Chen
- School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
| | - Zhi-Quan Chen
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
- Key Laboratory of Glycolipid Metabolic Diseases, Ministry of Education, Guangzhou, 510006, China
| | - Xiang-Lu Rong
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
- Key Laboratory of Glycolipid Metabolic Diseases, Ministry of Education, Guangzhou, 510006, China
| | - Jeremy E Turnbull
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Jiao Guo
- Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China
- Key Laboratory of Glycolipid Metabolic Diseases, Ministry of Education, Guangzhou, 510006, China
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He Y, Zhang H, Yang Y, Yu X, Zhang X, Xing Q, Zhang G. Using Metabolomics in Diabetes Management with Traditional Chinese Medicine: A Review. THE AMERICAN JOURNAL OF CHINESE MEDICINE 2022; 49:1813-1837. [PMID: 34961417 DOI: 10.1142/s0192415x21500865] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
The incidence of diabetes worldwide continues to rise, placing a huge economic and medical burden on human society. More than 90% of diabetic cases are type 2 diabetes (T2D). At present, the pathogenesis of T2D is not yet fully understood. Metabolomics uses high-resolution analytical techniques (typically NMR and MS) to help identify biomarkers associated with the risk of T2D and reveal potential pathogenesis. Many metabolites such as branched-chain amino acids (BCAAs), aromatic amino acids, glycine, 2-hydroxybutyric acid (2-HB), lysophosphatidylcholine (LPC) (18:2), and trehalose have proven to be biomarkers of T2D. Insulin resistance (IR) induced by BCAA in T2D mice is related to the activation of mammalian target of rapamycin (mTOR) and phosphorylation of insulin receptor substrate-1 (IRS1). Incomplete LCFA [Formula: see text]-oxidation promote acylcarnitine byproduct accumulation and stimulates proinflammatory NF[Formula: see text]B-related pathways to inhibit insulin action. Traditional Chinese Medicine (TCM) presents unique advantages in the treatment of T2D. Multiple metabolites and metabolic pathways have been identified in the treatment of TCM, providing valuable biomarkers and novel targets for drug therapy and pharmacological mechanism. Therefore, this paper reviews the modern achievements of metabolomics in T2D research and the progress of TCM management in recent years, in order to provide valuable information for related research.
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Affiliation(s)
- Yanling He
- Graduate School of Hebei University of Traditional, Chinese Medicine, Shijiazhuang 050091, P. R. China
| | - Hefang Zhang
- Graduate School of Hebei University of Traditional, Chinese Medicine, Shijiazhuang 050091, P. R. China.,Department of Endocrinology, First Affiliated Hospital of Hebei University of Traditional, Chinese Medicine, Shijiazhuang 050011, P. R. China
| | - Yufei Yang
- Graduate School of Hebei University of Traditional, Chinese Medicine, Shijiazhuang 050091, P. R. China
| | - Xianghui Yu
- Department of Endocrinology, First Affiliated Hospital of Hebei University of Traditional, Chinese Medicine, Shijiazhuang 050011, P. R. China
| | - Xiao Zhang
- Graduate School of Hebei University of Traditional, Chinese Medicine, Shijiazhuang 050091, P. R. China
| | - Qiaolin Xing
- Graduate School of Hebei University of Traditional, Chinese Medicine, Shijiazhuang 050091, P. R. China
| | - Gengliang Zhang
- Graduate School of Hebei University of Traditional, Chinese Medicine, Shijiazhuang 050091, P. R. China.,Department of Endocrinology, First Affiliated Hospital of Hebei University of Traditional, Chinese Medicine, Shijiazhuang 050011, P. R. China
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20
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Calderón C, Lämmerhofer M. Enantioselective metabolomics by liquid chromatography-mass spectrometry. J Pharm Biomed Anal 2022; 207:114430. [PMID: 34757254 DOI: 10.1016/j.jpba.2021.114430] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 10/08/2021] [Accepted: 10/12/2021] [Indexed: 12/13/2022]
Abstract
Metabolomics strives to capture the entirety of the metabolites in a biological system by comprehensive analysis, often by liquid chromatography hyphenated to mass spectrometry. A particular challenge thereby is the differentiation of structural isomers. Common achiral targeted and untargeted assays do not distinguish between enantiomers. This may lead to information loss. An increasing number of publications demonstrate that the enantiomeric ratio of certain metabolites can be meaningful biomarkers of certain diseases emphasizing the importance of introducing enantioselective analytical procedures in metabolomics. In this work, the state-of-the-art in the field of LC-MS based metabolomics is summarized with focus on developments in the recent decade. Methodologies, tagging strategies, workflows and general concepts are outlined. Selected biological applications in which enantioselective metabolomics has documented its usefulness are briefly discussed. In general, targeted enantioselective metabolomics assays are often based on a direct approach using chiral stationary phases (CSP) with polysaccharide derivatives, macrocyclic antibiotics, chiral crown ethers, chiral ion exchangers, donor-acceptor phases as chiral selectors. Rarely, these targeted assays focus on more than 20 analytes and usually are restricted to a certain metabolite class. In a variety of cases, pre-column derivatization of metabolites has been performed, especially for amino acids, to improve separation and detection sensitivity. Triple quadrupole instruments are the detection methods of first choice in targeted assays. Here, issues like matrix effect, absence of blank matrix impair accuracy of results. In selected applications, multiple heart cutting 2D-LC (RP followed by chiral separation) has been pursued to overcome this problem and alleviate bias due to interferences. Non-targeted assays, on the other hand, are based on indirect approach involving tagging with a chiral derivatizing agent (CDA). Besides classical CDAs numerous innovative reagents and workflows have been proposed and are discussed. Thereby, a critical issue for the accuracy is often neglected, viz. the validation of the enantiomeric impurity in the CDA. The majority of applications focus on amino acids, hydroxy acids, oxidized fatty acids and oxylipins. Some potential clinical applications are highlighted.
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Affiliation(s)
- Carlos Calderón
- Institute of Pharmaceutical Sciences, Pharmaceutical (Bio-)Analysis, University of Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany; Escuela de Química, Universidad de Costa Rica, San José 11501-2060, Costa Rica
| | - Michael Lämmerhofer
- Institute of Pharmaceutical Sciences, Pharmaceutical (Bio-)Analysis, University of Tübingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany.
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21
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Lu G, Yu X, Jiang W, Luo Q, Tong J, Fan S, Chai L, Gao D, Qiao T, Wang R, Deng C, Lv Z, Li D. Alterations of Gut Microbiome and Metabolite Profiles Associated With Anabatic Lipid Dysmetabolism in Thyroid Cancer. Front Endocrinol (Lausanne) 2022; 13:893164. [PMID: 35721748 PMCID: PMC9204252 DOI: 10.3389/fendo.2022.893164] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 04/21/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Currently, the high morbidity of individuals with thyroid cancer (TC) is an increasing health care burden worldwide. The aim of our study was to investigate the relationship among the gut microbiota community, metabolites, and the development of differentiated thyroid cancer. METHODS 16S rRNA gene sequencing and an integrated LC-MS-based metabolomics approach were performed to obtain the components and characteristics of fecal microbiota and metabolites from 50 patients with TC and 58 healthy controls (HCs). RESULTS The diversity and richness of the gut microbiota in the TC patients were markedly decreased. The composition of the gut microbiota was significantly altered, and the Bacteroides enterotype was the dominant enterotype in TC patients. Additionally, the diagnostic validity of the combined model (three genera and eight metabolites) and the metabolite model (six metabolites) were markedly higher than that of the microbial model (seven genera) for distinguishing TC patients from HCs. LEfSe analysis demonstrated that genera (g_Christensenellaceae_R-7_group, g_Eubacterium_coprostanoligenes_group) and metabolites [27-hydroxycholesterol (27HC), cholesterol] closely related to lipid metabolism were greatly reduced in the TC group. In addition, a clinical serum indicator (total cholesterol) and metabolites (27HC and cholesterol) had the strongest influence on the sample distribution. Furthermore, functional pathways related to steroid biosynthesis and lipid digestion were inhibited in the TC group. In the microbiota-metabolite network, 27HC was significantly related to metabolism-related microorganisms (g_Christensenellaceae_R-7_group). CONCLUSIONS Our research explored the characteristics of the gut microecology of patients with TC. The findings of this study will help to discover risk factors that affect the occurrence and development of TC in the intestinal microecology.
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Affiliation(s)
- Ganghua Lu
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Xiaqing Yu
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Wen Jiang
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Qiong Luo
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, China
| | - Junyu Tong
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, China
| | - Suyun Fan
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, China
| | - Li Chai
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, China
| | - Dingwei Gao
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Tingting Qiao
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Ru Wang
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Chengwen Deng
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Zhongwei Lv
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, China
- Imaging Clinical Medical Center, Tongji University School of Medicine, Shanghai, China
- Institute of Nuclear Medicine, Tongji University School of Medicine, Shanghai, China
- *Correspondence: Dan Li, ; Zhongwei Lv,
| | - Dan Li
- Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, China
- Institute of Nuclear Medicine, Tongji University School of Medicine, Shanghai, China
- *Correspondence: Dan Li, ; Zhongwei Lv,
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22
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Wu F, Liang P. Application of Metabolomics in Various Types of Diabetes. Diabetes Metab Syndr Obes 2022; 15:2051-2059. [PMID: 35860310 PMCID: PMC9289753 DOI: 10.2147/dmso.s370158] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/23/2022] [Indexed: 12/31/2022] Open
Abstract
Metabolomics is the analysis of numerous small molecules known as metabolites. Over the past few years, with the continuous development in metabolomics, it has been widely used in the detection, diagnosis, and treatment of diabetes and has demonstrated great benefits. At the same time, studies on diabetes and its complications have discovered the metabolic markers that are characteristic of diabetes. However, the pathogenesis of diabetes has yet to be clarified, as well as no complete cure. The mechanism of diabetes has not been completely elucidated, and its eradication treatment is not available. Thus, prevention of the onset of the disease and its treatment have become very important. In this review, we focused on the recent progress in the use of metabolites in diabetes and their complications, as well as understanding the impact of diabetes metabolites.
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Affiliation(s)
- Fangqin Wu
- Department of Burns and Plastic Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
| | - Pengfei Liang
- Department of Burns and Plastic Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China
- Correspondence: Pengfei Liang, Department of Burns and Plastic Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China, Tel +86-13875858144, Email
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23
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Zahn M, König G, Cuong Pham HV, Seroka B, Lazny R, Yang G, Ouerfelli O, Lotowski Z, Rohwerder T. Mechanistic details of the actinobacterial lyase-catalyzed degradation reaction of 2-hydroxyisobutyryl-CoA. J Biol Chem 2021; 298:101522. [PMID: 34952003 PMCID: PMC8760513 DOI: 10.1016/j.jbc.2021.101522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/16/2021] [Accepted: 12/19/2021] [Indexed: 11/28/2022] Open
Abstract
Actinobacterial 2-hydroxyacyl-CoA lyase reversibly catalyzes the thiamine diphosphate-dependent cleavage of 2-hydroxyisobutyryl-CoA to formyl-CoA and acetone. This enzyme has great potential for use in synthetic one-carbon assimilation pathways for sustainable production of chemicals, but lacks details of substrate binding and reaction mechanism for biochemical reengineering. We determined crystal structures of the tetrameric enzyme in the closed conformation with bound substrate, covalent postcleavage intermediate, and products, shedding light on active site architecture and substrate interactions. Together with molecular dynamics simulations of the covalent precleavage complex, the complete catalytic cycle is structurally portrayed, revealing a proton transfer from the substrate acyl Cβ hydroxyl to residue E493 that returns it subsequently to the postcleavage Cα-carbanion intermediate. Kinetic parameters obtained for mutants E493A, E493Q, and E493K confirm the catalytic role of E493 in the WT enzyme. However, the 10- and 50-fold reduction in lyase activity in the E493A and E493Q mutants, respectively, compared with WT suggests that water molecules may contribute to proton transfer. The putative catalytic glutamate is located on a short α-helix close to the active site. This structural feature appears to be conserved in related lyases, such as human 2-hydroxyacyl-CoA lyase 2. Interestingly, a unique feature of the actinobacterial 2-hydroxyacyl-CoA lyase is a large C-terminal lid domain that, together with active site residues L127 and I492, restricts substrate size to ≤C5 2-hydroxyacyl residues. These details about the catalytic mechanism and determinants of substrate specificity pave the ground for designing tailored catalysts for acyloin condensations for one-carbon and short-chain substrates in biotechnological applications.
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Affiliation(s)
- Michael Zahn
- Centre for Enzyme Innovation, School of Biological Sciences, Institute of Biological and Biomedical Sciences, University of Portsmouth, Portsmouth PO1 2DT, United Kingdom.
| | - Gerhard König
- Centre for Enzyme Innovation, School of Biological Sciences, Institute of Biological and Biomedical Sciences, University of Portsmouth, Portsmouth PO1 2DT, United Kingdom
| | - Huy Viet Cuong Pham
- Department of Environmental Microbiology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Barbara Seroka
- Faculty of Chemistry, University of Bialystok, K. Ciolkowskiego 1K, 15-245 Bialystok, Poland
| | - Ryszard Lazny
- Faculty of Chemistry, University of Bialystok, K. Ciolkowskiego 1K, 15-245 Bialystok, Poland
| | - Guangli Yang
- Organic Synthesis Core Facility, Memorial Sloan Kettering Cancer Center (MSKCC), New York, NY 10065, USA
| | - Ouathek Ouerfelli
- Organic Synthesis Core Facility, Memorial Sloan Kettering Cancer Center (MSKCC), New York, NY 10065, USA
| | - Zenon Lotowski
- Faculty of Chemistry, University of Bialystok, K. Ciolkowskiego 1K, 15-245 Bialystok, Poland
| | - Thore Rohwerder
- Department of Environmental Microbiology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany.
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24
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O'Kell AL, Wasserfall C, Guingab-Cagmat J, Webb-Roberston BJM, Atkinson MA, Garrett TJ. Targeted metabolomic analysis identifies increased serum levels of GABA and branched chain amino acids in canine diabetes. Metabolomics 2021; 17:100. [PMID: 34775536 PMCID: PMC8693811 DOI: 10.1007/s11306-021-01850-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Accepted: 10/29/2021] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Dogs with naturally occurring diabetes mellitus represent a potential model for human type 1 diabetes, yet significant knowledge voids exist in terms of the pathogenic mechanisms underlying the canine disorder. Untargeted metabolomic studies from a limited number of diabetic dogs identified similarities to humans with the disease. OBJECTIVE To expand and validate earlier metabolomic studies, identify metabolites that differ consistently between diabetic and healthy dogs, and address whether certain metabolites might serve as disease biomarkers. METHODS Untargeted metabolomic analysis via liquid chromatography-mass spectrometry was performed on serum from diabetic (n = 15) and control (n = 15) dogs. Results were combined with those of our previously published studies using identical methods (12 diabetic and 12 control dogs) to identify metabolites consistently different between the groups in all 54 dogs. Thirty-two candidate biomarkers were quantified using targeted metabolomics. Biomarker concentrations were compared between the groups using multiple linear regression (corrected P < 0.0051 considered significant). RESULTS Untargeted metabolomics identified multiple persistent differences in serum metabolites in diabetic dogs compared with previous studies. Targeted metabolomics showed increases in gamma amino butyric acid, valine, leucine, isoleucine, citramalate, and 2-hydroxyisobutyric acid in diabetic versus control dogs while indoxyl sulfate, N-acetyl-L-aspartic acid, kynurenine, anthranilic acid, tyrosine, glutamine, and tauroursodeoxycholic acid were decreased. CONCLUSION Several of these findings parallel metabolomic studies in both human diabetes and other animal models of this disease. Given recent studies on the role of GABA and branched chain amino acids in human diabetes, the increase in serum concentrations in canine diabetes warrants further study of these metabolites as potential biomarkers, and to identify similarity in mechanisms underlying this disease in humans and dogs.
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Affiliation(s)
- Allison L O'Kell
- Department of Small Animal Clinical Sciences, College of Veterinary Medicine, The University of Florida, 2015 SW 16th Ave, Box 100116, Gainesville, FL, 32608, USA.
| | - Clive Wasserfall
- Department of Pathology, Immunology, and Laboratory Medicine, The University of Florida, Gainesville, FL, USA
| | - Joy Guingab-Cagmat
- Southeast Center for Integrated Metabolomics, Clinical and Translational Science Institute, The University of Florida, Gainesville, FL, USA
| | - Bobbie-Jo M Webb-Roberston
- Department of Pathology, Immunology, and Laboratory Medicine, The University of Florida, Gainesville, FL, USA
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Mark A Atkinson
- Department of Pathology, Immunology, and Laboratory Medicine, The University of Florida, Gainesville, FL, USA
| | - Timothy J Garrett
- Department of Pathology, Immunology, and Laboratory Medicine, The University of Florida, Gainesville, FL, USA
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Sun G, Jiang F, Hu S, Cheng H, Qu L, Tao Y, Ma B. Metabolomic analysis reveals potential biomarkers and serum metabolomic profiling in spontaneous intracerebral hemorrhage patients using UPLC/quadrupole time-of-flight MS. Biomed Chromatogr 2021; 36:e5241. [PMID: 34505712 DOI: 10.1002/bmc.5241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/01/2021] [Accepted: 09/02/2021] [Indexed: 11/08/2022]
Abstract
Spontaneous intracerebral hemorrhage (ICH) accounts for 10-20% of all strokes and contributes to higher mortalities and severe disabilities. The aims of this study were, therefore, to characterize novel biomarkers, metabolic disruptions, and mechanisms involving ICH. A total 30 ICH patients and 30 controls were enrolled in the study, and their clinical characteristics were analyzed. Nontargeted metabolomic analysis was conducted using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF). Multivariate statistical analysis and receiver operating characteristic curve analysis were used for screening and evaluating the predictive ability of biomarkers. ICH patients showed significantly higher systolic blood pressure, diastolic blood pressure, blood glucose levels, white blood cell counts, neutrophil count, percentage of neutrophils and globulin and a lower albumin/globin ratio when compared with controls. In sum, 11 important metabolites were identified, which were associated with disruption of fatty acid oxidation and sphingolipid and phospholipid metabolism, as well as increased inflammation, oxidative stress, and vascular pathologies. Further multiple logistic regression analyses of these metabolites showed that l-carnitine and phosphatidylcholine (20:3/22:6) have potential as biomarkers of ICH, and the area under the curve, sensitivity, specificity were 0.974, 90%, and 93%, respectively. These findings provide insights into the pathogenesis, early prevention, and diagnosis of ICH.
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Affiliation(s)
- Guozhang Sun
- Department of Neurosurgery, Second Affiliated Hospital of Harbin Medical University, Harbin, China.,Department of Neurosurgery, Heilongjiang Provincial Hospital, Harbin, China
| | - Fengling Jiang
- Department of Internal Neurology, Harbin Xiangfang District People's Hospital, Harbin, China
| | - Shaoshan Hu
- Department of Neurosurgery, Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Huakun Cheng
- Department of Neurosurgery, Heilongjiang Provincial Hospital, Harbin, China
| | - Lianlong Qu
- Department of Neurosurgery, Heilongjiang Provincial Hospital, Harbin, China
| | - Yu Tao
- Department of Neurosurgery, Heilongjiang Provincial Hospital, Harbin, China
| | - Bowen Ma
- Department of Neurosurgery, Heilongjiang Provincial Hospital, Harbin, China
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Metabolomics in Bariatric Surgery: Towards Identification of Mechanisms and Biomarkers of Metabolic Outcomes. Obes Surg 2021; 31:4564-4574. [PMID: 34318371 DOI: 10.1007/s11695-021-05566-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 06/17/2021] [Accepted: 06/24/2021] [Indexed: 12/27/2022]
Abstract
Bariatric surgery has been widely performed for the treatment of obesity and type 2 diabetes. Efforts have been made to investigate the mechanisms underlying the metabolic effects achieved by bariatric surgery and to identify candidates who will benefit from this surgery. Metabolomics, which includes comprehensive profiling of metabolites in biological samples, has been utilized for various disease entities to discover pathophysiological metabolic pathways and biomarkers predicting disease progression or prognosis. Over the last decade, metabolomic studies on patients undergoing bariatric surgery have identified significant biomarkers related to metabolic effects. This review describes the significance, progress, and challenges for the future of metabolomics in the area of bariatric surgery.
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Liu R, Bao ZX, Zhao PJ, Li GH. Advances in the Study of Metabolomics and Metabolites in Some Species Interactions. Molecules 2021; 26:3311. [PMID: 34072976 PMCID: PMC8197931 DOI: 10.3390/molecules26113311] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/24/2021] [Accepted: 05/28/2021] [Indexed: 12/15/2022] Open
Abstract
In the natural environment, interactions between species are a common natural phenomena. The mechanisms of interaction between different species are mainly studied using genomic, transcriptomic, proteomic, and metabolomic techniques. Metabolomics is a crucial part of system biology and is based on precision instrument analysis. In the last decade, the emerging field of metabolomics has received extensive attention. Metabolomics not only provides a qualitative and quantitative method for studying the mechanisms of interactions between different species, but also helps clarify the mechanisms of defense between the host and pathogen, and to explore new metabolites with various biological activities. This review focuses on the methods and progress of interspecies metabolomics. Additionally, the prospects and challenges of interspecies metabolomics are discussed.
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Affiliation(s)
| | | | | | - Guo-Hong Li
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, and Key Laboratory for Microbial Resources of the Ministry of Education, Yunnan University, Kunming 650091, China; (R.L.); (Z.-X.B.); (P.-J.Z.)
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Abstract
Life expectancy, and longevity have been increasing in recent years. However, this is, in most cases, accompanied by age-related diseases. Thus, it became essential to better understand the mechanisms inherent to aging, and to establish biomarkers that characterize this physiological process. Among all biomolecules, lipids appear to be a good target for the study of these biomarkers. In fact, some lipids have already been associated with age-related diseases. With the development of analytical techniques such as Mass Spectrometry, and Nuclear Magnetic Resonance, Lipidomics has been increasingly used to study pathological, and physiological states of an organism. Thus, the study of serum, and plasma lipidome in centenarians, and elderly individuals without age-related diseases can be a useful tool for the identification of aging biomarkers, and to understand physiological aging, and longevity. This review focus on the importance of lipids as biomarkers of aging, and summarize the changes in the lipidome that have been associated with aging, and longevity.
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Demyanova EV, Shcherbakova ES, Sall TS, Bakulin IG, Vakhitov TY, Sitkin SI. Non-targeted Serum Metabolomics Identifies Candidate Biomarkers Panels Associated with Nonalcoholic Fatty Liver Disease: A Pilot Study in Russian Male Patients. THE OPEN BIOMARKERS JOURNAL 2021; 11:17-27. [DOI: 10.2174/1875318302111010017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 01/04/2021] [Accepted: 01/07/2021] [Indexed: 09/26/2023]
Abstract
Aims:
The aim of the present study was to explore changes in the serum metabolome of patients with NAFLD relative to healthy controls to identify biomarkers associated with steatosis or Non-Alcoholic Steatohepatitis (NASH).
Background:
The serum metabolome reflects changes at the organismal level. This is especially important in Non-Alcoholic Liver Disease (NAFLD), where changes in hormones, cytokines, enzymes and other metabolic alterations can affect the liver, as well as adipose tissue, skeletal muscle and other systems.
Objective:
The objectives were to conduct non-targeted serum metabolomics, data processing, and identification of candidate biomarkers, as well as panels and assessment of their prognostic value.
Materials and Methods:
Non-targeted metabolomic analysis of blood serum samples from 21 male patients with NAFLD (simple steatosis or NASH) and seven male Control group was performed using gas chromatography-mass spectrometry.
Results:
A total of 319 serum metabolites were detected in NAFLD and Control groups, several of which differed significantly between groups. The most discriminating biomarkers were 3-hydroxybutyric acid, 2-hydroxybutyric acid, 2,3-dihydroxybutyric acid, arabitol and 3-methyl-2-oxovaleric acid. Using a panel of three, four or more markers could distinguish patients with NAFLD from controls, and patients with NASH from those with simple steatosis.
Conclusion:
We identified candidate biomarkers for simple steatosis and NASH. Since NAFLD is a multifactorial disease, it is preferable to use a marker panel rather than individual metabolites. Markers may not only result from dysregulation of metabolic pathways in patients with NAFLD, they may also reflect adaptive responses to disease, including functional changes in the intestinal microbiota.
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Shuai M, Zuo LSY, Miao Z, Gou W, Xu F, Jiang Z, Ling CW, Fu Y, Xiong F, Chen YM, Zheng JS. Multi-omics analyses reveal relationships among dairy consumption, gut microbiota and cardiometabolic health. EBioMedicine 2021; 66:103284. [PMID: 33752125 PMCID: PMC7985282 DOI: 10.1016/j.ebiom.2021.103284] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 02/19/2021] [Accepted: 03/01/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Little is known about the interplay among dairy intake, gut microbiota and cardiometabolic health in human prospective cohort studies. METHODS The present study included 1780 participants from the Guangzhou Nutrition and Health Study. We examined the prospective association between habitual dairy consumption (total dairy, milk, yogurt) and gut microbial composition using linear regression after adjusting for socio-demographic, lifestyle and dietary factors. The cross-sectional association of dairy-associated microbial features with cardiometabolic risk factors was examined with a linear regression model, adjusting for potential confounders. Serum metabolomic profiles were analyzed by partial correlation analysis. FINDINGS There was a significant overall difference in gut microbial community structure (β-diversity) comparing the highest with the lowest category for each of total dairy, milk and yogurt (P < 0.05). We observed that dairy-associated microbes and α-diversity indices were inversely associated with blood triglycerides, while positively associated with high-density lipoprotein cholesterol. A follow-up metabolomics analysis revealed the association of targeted serum metabolites with dairy-microbial features and cardiometabolic traits. Specifically, 2-hydroxy-3-methylbutyric acid, 2-hydroxybutyric acid and L-alanine were inversely associated with dairy-microbial score, while positively associated with triglycerides (FDR-corrected P < 0.1). INTERPRETATION Dairy consumption is associated with the gut microbial composition and a higher α-diversity, which provides new insights into the understanding of dairy-gut microbiota interactions and their relationship with cardiometabolic health. FUNDING This work was supported by the National Natural Science Foundation of China, Zhejiang Ten-thousand Talents Program, Westlake University and the 5010 Program for Clinical Researches of the Sun Yat-sen University.
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Affiliation(s)
- Menglei Shuai
- School of Life Sciences, Fudan University, Shanghai, China; Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Luo-Shi-Yuan Zuo
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zelei Miao
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Wanglong Gou
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Fengzhe Xu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Zengliang Jiang
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Chu-Wen Ling
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yuanqing Fu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Feng Xiong
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yu-Ming Chen
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Ju-Sheng Zheng
- School of Life Sciences, Fudan University, Shanghai, China; Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
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31
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Yang JS, Lee HW, Song H, Ha JH. Volatile Metabolic Markers for Monitoring Pectobacterium carotovorum subsp. carotovorum Using Headspace Solid-Phase Microextraction Coupled with Gas Chromatography-Mass Spectrometry. J Microbiol Biotechnol 2021; 31:70-78. [PMID: 33203818 PMCID: PMC9705696 DOI: 10.4014/jmb.2009.09028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 11/02/2020] [Accepted: 11/11/2020] [Indexed: 12/15/2022]
Abstract
Identifying the extracellular metabolites of microorganisms in fresh vegetables is industrially useful for assessing the quality of processed foods. Pectobacterium carotovorum subsp. carotovorum (PCC) is a plant pathogenic bacterium that causes soft rot disease in cabbages. This microbial species in plant tissues can emit specific volatile molecules with odors that are characteristic of the host cell tissues and PCC species. In this study, we used headspace solid-phase microextraction followed by gas chromatography coupled with mass spectrometry (HS-SPME-GC-MS) to identify volatile compounds (VCs) in PCC-inoculated cabbage at different storage temperatures. HS-SPME-GC-MS allowed for recognition of extracellular metabolites in PCC-infected cabbages by identifying specific volatile metabolic markers. We identified 4-ethyl-5-methylthiazole and 3-butenyl isothiocyanate as markers of fresh cabbages, whereas 2,3-butanediol and ethyl acetate were identified as markers of soft rot in PCC-infected cabbages. These analytical results demonstrate a suitable approach for establishing non-destructive plant pathogen-diagnosis techniques as alternatives to standard methods, within the framework of developing rapid and efficient analytical techniques for monitoring plant-borne bacterial pathogens. Moreover, our techniques could have promising applications in managing the freshness and quality control of cabbages.
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Affiliation(s)
- Ji-Su Yang
- Hygienic Safety and Analysis Center, World Institute of Kimchi, Gwangju 61755, Republic of Korea
| | - Hae-Won Lee
- Hygienic Safety and Analysis Center, World Institute of Kimchi, Gwangju 61755, Republic of Korea
| | - Hyeyeon Song
- Hygienic Safety and Analysis Center, World Institute of Kimchi, Gwangju 61755, Republic of Korea
| | - Ji-Hyoung Ha
- Hygienic Safety and Analysis Center, World Institute of Kimchi, Gwangju 61755, Republic of Korea,Corresponding author Phone: +82-62-610-1845 E-mail:
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32
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Wang L, Zhang Y, Liu X, Zhao X, Ouyang Y, Qiu G, Lv W, Zheng F, Wang Q, Lu X, Peng X, Wu T, Lehmann R, Wang C, Jia W, Xu G. Metabolite Triplet in Serum Improves the Diagnostic Accuracy of Prediabetes and Diabetes Screening. J Proteome Res 2020; 20:1005-1014. [PMID: 33347754 DOI: 10.1021/acs.jproteome.0c00786] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Large-scale population screenings are not feasible by applying laborious oral glucose tolerance tests, but using fasting blood glucose (FPG) and glycated hemoglobin (HbA1c), a considerable number of diagnoses are missed. A novel marker is urgently needed to improve the diagnostic accuracy of broad-scale diabetes screening in easy-to-collect blood samples. In this study, by applying a novel knowledge-based, multistage discovery and validation strategy, we scaled down from 108 diabetes-associated metabolites to a diagnostic metabolite triplet (Met-T), namely hexose, 2-hydroxybutyric/2-hydroxyisobutyric acid, and phenylalanine. Met-T showed in two independent cohorts, each comprising healthy controls, prediabetic, and diabetic individuals, distinctly higher diagnostic sensitivities for diabetes screening than FPG alone (>79.6 vs <68%). Missed diagnoses decreased from >32% using fasting plasma glucose down to <20.4%. Combining Met-T and fasting plasma glucose further improved the diagnostic accuracy. Additionally, a positive association of Met-T with future diabetes risk was found (odds ratio: 1.41; p = 1.03 × 10-6). The results reveal that missed prediabetes and diabetes diagnoses can be markedly reduced by applying Met-T alone or in combination with FPG and it opens perspectives for higher diagnostic accuracy in broad-scale diabetes-screening approaches using easy to collect sample materials.
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Affiliation(s)
- Lichao Wang
- State Key Laboratory of Fine Chemicals, Dalian University of Technology, Dalian 116024, China.,CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yinan Zhang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China
| | - Yang Ouyang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Gaokun Qiu
- MOE Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Wangjie Lv
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fujian Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - QingQing Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China
| | - Xiaojun Peng
- State Key Laboratory of Fine Chemicals, Dalian University of Technology, Dalian 116024, China
| | - Tangchun Wu
- MOE Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Rainer Lehmann
- Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tuebingen, Hoppe-Seyler-Strasse 3, Tuebingen 72076, Germany.,Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Zentrum Muenchen at the University of Tuebingen, Tuebingen 72076, Germany.,German Center for Diabetes Research (DZD), Tübingen 72076, Germany
| | - Congrong Wang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.,Department of Endocrinology, Shanghai Fourth People's Hospital Affiliated to Tongji University, Shanghai 200434, China
| | - Weiping Jia
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China
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Li S, Liu J, Zhou J, Wang Y, Jin F, Chen X, Yang J, Chen Z. Urinary Metabolomic Profiling Reveals Biological Pathways and Predictive Signatures Associated with Childhood Asthma. J Asthma Allergy 2020; 13:713-724. [PMID: 33376359 PMCID: PMC7755329 DOI: 10.2147/jaa.s281198] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 11/20/2020] [Indexed: 12/16/2022] Open
Abstract
Background Despite considerable efforts, the pathogenic mechanisms of asthma are still incompletely understood, due to its heterogeneous nature. However, metabolomics can offer a global view of a biological system, making it a valuable tool for further elucidation of mechanisms and biomarker discovery in asthma. Methods GC-MS-based metabolomic analysis was conducted for comparison of urine metabolic profiles between asthmatic children (n=30) and healthy controls (n=30). Results An orthogonal projections to latent structures discriminant-analysis model revealed a clear separation of the asthma and control groups (R 2 x =0.137, R 2 y =0.947, Q 2=0.82). A total of 20 differential metabolites were identified as discriminant factors, of which eleven were significantly increased and nine decreased in the asthma group compared to the control group. Pathway-enrichment analysis based on these differential metabolites indicated that sphingolipid metabolism, protein biosynthesis, and citric acid cycle were strongly associated with asthma. Among the identified metabolites, 2-hydroxybutanoic acid showed excellent discriminatory performance for distinguishing asthma from healthy controls, with an AUC of 0.969. Conclusion Our study revealed significant changes in the urine metabolome of asthma patients. Several perturbed pathways (eg, sphingolipid metabolism and citric acid cycle) may be related to asthma pathogenesis, and 2-hydroxybutanoic acid could serve as a potential biomarker for asthma diagnosis.
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Affiliation(s)
- Shuxian Li
- Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang 310052, China
| | - Jinling Liu
- Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang 310052, China
| | - Junfen Zhou
- Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang 310052, China.,Department of Pediatrics, Wenling Maternal and Child Health Care Hospital, Wenling, Zhejiang 317500, China
| | - Yingshuo Wang
- Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang 310052, China
| | - Fang Jin
- Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang 310052, China
| | - Xiaoyang Chen
- Developmental and Behavioral Department, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang 310052, China
| | - Jun Yang
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, First Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang 310013, China.,Department of Toxicology, Hangzhou Normal University School of Public Health, Hangzhou, Zhejiang 310016, China
| | - Zhimin Chen
- Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang 310052, China
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Cui X, Wang R, Hua Z, Yin H, Wu Z, Lian R, Chen G, Liang C, Zhang Y. Estimation of synthetic route of methamphetamine samples seized in China by direct analysis in real time with high-resolution mass spectrometry and chemometric analysis of organic impurities. Microchem J 2020. [DOI: 10.1016/j.microc.2020.105481] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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35
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Han D, Shi L, Pan H. Plasma metabolomics analysis of the effects of drinking soda water on hyperglycemia mice using ultrahigh-pressure liquid chromatography-quadrupole-time of flight-mass spectrometry. Biomed Chromatogr 2020; 35:e5032. [PMID: 33220100 DOI: 10.1002/bmc.5032] [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: 08/05/2020] [Revised: 11/12/2020] [Accepted: 11/17/2020] [Indexed: 11/09/2022]
Abstract
The aim of this study was to evaluate the effects of a natural soda water [Shi Han Quan (SHQ)] on hyperglycemia and plasma metabolic profiling and explore the mechanism using metabolomics techniques. Kun-Ming mice weighing 26 ± 2 g were used for the hyperglycemia animal model with alloxan and divided into control, hyperglycemia (HG), and HG + SHQ soda water (SHQ) groups. The experiment lasted for 30 days. The plasma metabolomic profiling of mice was determined using ultrahigh-pressure liquid chromatography-quadrupole-time of flight-mass spectrometry. After the mice drank SHQ soda water, the levels of insulin and blood glucose were significantly lower in the SHQ group compared with the control group, and the level of insulin sensitivity [insulin sensitivity index (ISI)] was significantly higher in the SHQ group compared with the HG group. The mice in the different groups after SHQ intervention could be separated into distinct clusters, and nine major plasma metabolites with significant differences between groups were found closely associated with blood glucose and ISI. The metabolic pathway analysis of these metabolites involved abnormal fatty acid oxidation and phospholipid, acylcarnitine, and corticoid metabolism. The results suggested the metabolic changes and possible mechanism of SHQ improving the alloxan-induced HG, and the findings provided insights into the prevention and control of HG and diabetes.
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Affiliation(s)
- Dan Han
- College of Medical Technology, Shanghai University of Medicine & Health Sciences, Shanghai, China
| | - Litian Shi
- Harbin Greenstone Water Research Institute, Harbin, China
| | - Hongzhi Pan
- Collaborative Scientific Research Center, Shanghai University of Medicine & Health Sciences, Shanghai, China
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36
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Wu ZE, Fraser K, Kruger MC, Sequeira IR, Yip W, Lu LW, Plank LD, Murphy R, Cooper GJS, Martin JC, Poppitt SD. Metabolomic signatures for visceral adiposity and dysglycaemia in Asian Chinese and Caucasian European adults: the cross-sectional TOFI_Asia study. Nutr Metab (Lond) 2020; 17:95. [PMID: 33292338 PMCID: PMC7667766 DOI: 10.1186/s12986-020-00518-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 10/20/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Asian Chinese are more susceptible to deposition of visceral adipose tissue (VAT) and type 2 diabetes (T2D) development than European Caucasians when matched for gender, age and body mass index (BMI). Our aims were: (i) characterise the ethnicity-specific metabolomic signature of visceral adiposity measured by dual energy X-ray absorptiometry (DXA) and fasting plasma glucose (FPG), and (ii) identify individuals susceptible to worse metabolic health outcomes. METHODS Fasting plasma samples from normoglycaemic (n = 274) and prediabetic (n = 83) participants were analysed with liquid chromatography-mass spectrometry using untargeted metabolomics. Multiple linear regression adjusting for age, gender and BMI was performed to identify metabolites associated with FPG and VAT calculated as percentage of total body fat (%VATTBF) in each ethnic group. Metabolic risk groups in each ethnicity were stratified based on the joint metabolomic signature for FPG and %VATTBF and clinically characterised using partial least squares-discriminant analysis (PLS-DA) and t-tests. RESULTS FPG was correlated with 40 and 110 metabolites in Caucasians and Chinese respectively, with diglyceride DG(38:5) (adjusted β = 0.29, p = 3.00E-05) in Caucasians and triglyceride TG(54:4) (adjusted β = 0.28, p = 2.02E-07) in Chinese being the most significantly correlated metabolite based on the p-value. %VATTBF was correlated with 85 and 119 metabolites in Caucasians and Chinese respectively, with TG(56:2) (adjusted β = 0.3, p = 8.25E-09) in Caucasians and TG(58:3) (adjusted β = 0.25, p = 2.34E-08) in Chinese being the most significantly correlated. 24 metabolites associated with FPG were common to both ethnicities including glycerolipid species. 67 metabolites associated with %VATTBF were common to both ethnicities including positive correlations with dihydroceramide, sphingomyelin, glycerolipid, phosphatidylcholine, phosphatidylethnolamine, and inverse correlations with ether-linked phosphatidylcholine. Participant re-stratification found greater total and central adiposity, worse clinical lipid profiles, higher serum glucoregulatory peptides and liver enzymes in normal fasting glucose (NFG) individuals with a prediabetic metabolomic profile than NFG individuals with a normoglycaemic metabolomic profile in both ethnicities. CONCLUSIONS Untargeted metabolomics identified common and disparate metabolites associated with FPG and %VATTBF, with an ethnic-dimorphic signature for these metabolic traits. These signatures could improve risk stratification and identify NFG individuals with an adverse cardiometabolic and T2D risk profile.
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Affiliation(s)
- Zhanxuan E Wu
- Food Nutrition and Health, Food and Bio-Based Products, AgResearch Limited, Palmerston North, 4442, New Zealand.,School of Health Sciences, Massey University, Palmerston North, 4442, New Zealand.,High-Value Nutrition National Science Challenge, Auckland, New Zealand
| | - Karl Fraser
- Food Nutrition and Health, Food and Bio-Based Products, AgResearch Limited, Palmerston North, 4442, New Zealand. .,High-Value Nutrition National Science Challenge, Auckland, New Zealand. .,Riddet Institute, Massey University, Palmerston North, 4442, New Zealand.
| | - Marlena C Kruger
- School of Health Sciences, Massey University, Palmerston North, 4442, New Zealand.,Riddet Institute, Massey University, Palmerston North, 4442, New Zealand
| | - Ivana R Sequeira
- High-Value Nutrition National Science Challenge, Auckland, New Zealand.,Human Nutrition Unit, School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand
| | - Wilson Yip
- High-Value Nutrition National Science Challenge, Auckland, New Zealand.,Human Nutrition Unit, School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand
| | - Louise W Lu
- High-Value Nutrition National Science Challenge, Auckland, New Zealand.,Human Nutrition Unit, School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand
| | - Lindsay D Plank
- Department of Surgery, University of Auckland, Auckland, 1010, New Zealand
| | - Rinki Murphy
- High-Value Nutrition National Science Challenge, Auckland, New Zealand.,Department of Medicine, School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand
| | - Garth J S Cooper
- Department of Medicine, School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand.,Centre for Advanced Discovery and Experimental Therapeutics, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9NT, UK
| | | | - Sally D Poppitt
- High-Value Nutrition National Science Challenge, Auckland, New Zealand.,Riddet Institute, Massey University, Palmerston North, 4442, New Zealand.,Human Nutrition Unit, School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand.,Department of Medicine, School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand
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Chen L, Zhong F, Zhu J. Bridging Targeted and Untargeted Mass Spectrometry-Based Metabolomics via Hybrid Approaches. Metabolites 2020; 10:E348. [PMID: 32867165 PMCID: PMC7570162 DOI: 10.3390/metabo10090348] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 08/19/2020] [Accepted: 08/23/2020] [Indexed: 01/11/2023] Open
Abstract
This mini-review aims to discuss the development and applications of mass spectrometry (MS)-based hybrid approaches in metabolomics. Several recently developed hybrid approaches are introduced. Then, the overall workflow, frequently used instruments, data handling strategies, and applications are compared and their pros and cons are summarized. Overall, the improved repeatability and quantitative capability in large-scale MS-based metabolomics studies are demonstrated, in comparison to either targeted or untargeted metabolomics approaches alone. In summary, we expect this review to serve as a first attempt to highlight the development and applications of emerging hybrid approaches in metabolomics, and we believe that hybrid metabolomics approaches could have great potential in many future studies.
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Affiliation(s)
- Li Chen
- Department of Human Sciences, The Ohio State University, Columbus, OH 43210, USA;
- James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
| | - Fanyi Zhong
- Department of Chemistry and Biochemistry, Miami University, Oxford, OH 45056, USA;
| | - Jiangjiang Zhu
- Department of Human Sciences, The Ohio State University, Columbus, OH 43210, USA;
- James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA
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38
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Di Giovanni N, Meuwis MA, Louis E, Focant JF. Specificity of metabolic colorectal cancer biomarkers in serum through effect size. Metabolomics 2020; 16:88. [PMID: 32789702 DOI: 10.1007/s11306-020-01707-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 07/30/2020] [Indexed: 02/08/2023]
Abstract
INTRODUCTION Colorectal cancer is one of the most diagnosed cancers, leading to numerous deaths. In addition to existing screening methods, metabolic profiling could help both to diagnose and to understand the various states of the disease. OBJECTIVES Find specific candidate biomarkers (CB) in serum of patients with colorectal cancer (CRC), in comparison to the situation after remission (R-CRC), evaluated on distinct patients. METHODS All serum samples were analyzed using comprehensive two-dimensional gas chromatography (GC × GC) coupled to high resolution time of flight mass spectrometry (TOF-MS) through an optimized and validated untargeted analytical method regulated by a quality control (QC) system. First, we used a specific multi-approaches data (pre)processing workflow to highlight, annotate and assess the performances of the most altered metabolites between CRC patients (n = 18) and healthy control samples (HC, n = 19) specifically matched for age and gender, two of the most influential confounding factors. On the contrary, due to the difficulty to control for all clinical and demographic traits when sampling small cohorts, the samples from patients in remission (n = 17) were not matched. Because of the consequent risk of bias, the usual null hypothesis significance tests (NHST) could not be applied reliably. Therefore, we compared the R-CRC samples to another specifically matched group of healthy controls (R-HC, n = 17), and used this comparison to indirectly address the difference between patients with colorectal cancer and patients in remission through a measure called effect size (ES) whose methodological aspects were investigated. RESULTS 24 candidate biomarkers were found significantly altered and able to discriminate the CRC and HC samples efficiently (Receiver Operating Characteristic (ROC) area under the curve (AUC) of 0.86, sensitivity and specificity of 0.72 and 0.78). 10 of those were found to have signals close to healthy levels in the R-CRC samples and were therefore specific to colorectal cancer. In the point-biserial case studied here, r-like (strength of association) and d-like (standardized mean difference) ES were directly convertible and only linear and rank-based ES were different. We therefore used and recommend Hedges' g, Spearman's rho and Kendall's tau, along with an unstandardized ES. The confidence intervals, that quantify the uncertainty of the measure, were well represented through scatterplots and distribution curves. CONCLUSION The candidate biomarkers found, along with their specificity, could help for the detection of colorectal cancer, the diagnosis of remission, and for the understanding of its pathophysiology, after proper validation on independent cohorts. The effect size, here applied on a MS global profiling data set, is an ideal complement to NHST and a useful tool to compare and combine distinct cohorts, within a study as well as between studies (meta-analysis).
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Affiliation(s)
- Nicolas Di Giovanni
- Department of Chemistry, Organic & Biological Analytical Chemistry Group, University of Liège, Allée du 6 août, B6c, B-4000, Liège (Sart Tilman), Belgium
| | - Marie-Alice Meuwis
- GIGA Institute, Translational Gastroenterology and CHU de Liège, Hepato-Gastroenterology and Digestive Oncology, University of Liège, Quartier Hôpital, Avenue de l'hôpital 13, B34-35, B-4000, Liège, Belgium
| | - Edouard Louis
- GIGA Institute, Translational Gastroenterology and CHU de Liège, Hepato-Gastroenterology and Digestive Oncology, University of Liège, Quartier Hôpital, Avenue de l'hôpital 13, B34-35, B-4000, Liège, Belgium
| | - Jean-François Focant
- Department of Chemistry, Organic & Biological Analytical Chemistry Group, University of Liège, Allée du 6 août, B6c, B-4000, Liège (Sart Tilman), Belgium.
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Bagheri M, Tiwari HK, Murillo AL, Al-Tobasei R, Arnett DK, Kind T, Barupal DK, Fan S, Fiehn O, O'connell J, Montasser M, Aslibekyan S, Irvin MR. A lipidome-wide association study of the lipoprotein insulin resistance index. Lipids Health Dis 2020; 19:153. [PMID: 32586392 PMCID: PMC7318473 DOI: 10.1186/s12944-020-01321-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 06/10/2020] [Indexed: 12/30/2022] Open
Abstract
Background The lipoprotein insulin resistance (LPIR) score was shown to predict insulin resistance (IR) and type 2 diabetes (T2D) in healthy adults. However, the molecular basis underlying the LPIR utility for classification remains unclear. Objective To identify small molecule lipids associated with variation in the LPIR score, a weighted index of lipoproteins measured by nuclear magnetic resonance, in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study (n = 980). Methods Linear mixed effects models were used to test the association between the LPIR score and 413 lipid species and their principal component analysis-derived groups. Significant associations were tested for replication with homeostatic model assessment-IR (HOMA-IR), a phenotype correlated with the LPIR score (r = 0.48, p < 0.001), in the Heredity and Phenotype Intervention (HAPI) Heart Study (n = 590). Results In GOLDN, 319 lipids were associated with the LPIR score (false discovery rate-adjusted p-values ranging from 4.59 × 10− 161 to 49.50 × 10− 3). Factors 1 (triglycerides and diglycerides/storage lipids) and 3 (mixed lipids) were positively (β = 0.025, p = 4.52 × 10− 71 and β = 0.021, p = 5.84 × 10− 41, respectively) and factor 2 (phospholipids/non-storage lipids) was inversely (β = − 0.013, p = 2.28 × 10− 18) associated with the LPIR score. These findings were replicated for HOMA-IR in the HAPI Heart Study (β = 0.10, p = 1.21 × 10− 02 for storage, β = − 0.13, p = 3.14 × 10− 04 for non-storage, and β = 0.19, p = 8.40 × 10− 07 for mixed lipids). Conclusions Non-storage lipidomics species show a significant inverse association with the LPIR metabolic dysfunction score and present a promising focus for future therapeutic and prevention studies.
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Affiliation(s)
- Minoo Bagheri
- Department of Epidemiology, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL, 35294, USA.,Department of Cardiovascular Medicine, Vanderbilt University Medical center, Nashville, TN, USA
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Anarina L Murillo
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Rafet Al-Tobasei
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Donna K Arnett
- Dean's Office, School of Public Health, University of Kentucky, Lexington, KY, USA
| | - Tobias Kind
- West coast metabolomics center, Davis, CA, USA
| | | | - Sili Fan
- West coast metabolomics center, Davis, CA, USA
| | | | - Jeff O'connell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland, School of Medicine, Baltimore, MD, USA
| | - May Montasser
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland, School of Medicine, Baltimore, MD, USA
| | - Stella Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL, 35294, USA.
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham, 1665 University Blvd, Birmingham, AL, 35294, USA
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Gómez E, Muñoz M, Gatien J, Carrocera S, Martín-González D, Salvetti P. Metabolomic identification of pregnancy-specific biomarkers in blood plasma of BOS TAURUS beef cattle after transfer of in vitro produced embryos. J Proteomics 2020; 225:103883. [PMID: 32574609 DOI: 10.1016/j.jprot.2020.103883] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Revised: 06/12/2020] [Accepted: 06/16/2020] [Indexed: 12/30/2022]
Abstract
Blood biomarkers may help to predict pregnancy in recipients of in vitro produced (IVP) embryos. Using 1H nuclear magnetic resonance, we quantified 36 metabolites in the blood plasma of recipients (90% heifers, healthy, 1.95 years on average at the time of 1st embryo transfer -ET-) collected at Day-0 (estrus) and Day-7 (before ET time). First, IVP embryos were transferred to Asturiana de los Valles recipients as fresh (F) (N = 26) and vitrified/warmed (V/W) (N = 48) (discovery groups). Only at estrus, we discovered 4, 11, and 5 (F-ET), and 2, 2, and 4 (V/W-ET) metabolites that predicted pregnancy on Day-40, Day-62 and calving time, respectively (ROC-AUC > 0.700; P < .05). Thereafter, validation was performed in independent samples (N = 67 F and N = 63 V/W) of three cattle breeds by an index of overall classification accuracy (OCA>0.650, P < .05). The numbers of candidate biomarkers validated were 2, 9 and 1 (F-ET) and 2, 2, and 3 (V/W-ET) on Day 40, Day-62 and calving time. Relevant metabolites were validated at the three (2-Oxoglutaric acid (F-ET), and 2-Hydroxybutyric acid and Dimethylamine (V/W-ET)) and two pregnancy endpoints (Ketoleucine (F-ET); Day-40 and Day-62) analysed. Fatty acid degradation and oxidative metabolism were enriched in pregnant recipients. The candidate biomarkers identified can improve embryo-recipient selection. SIGNIFICANCE: We identified, for the first time, reliable pregnancy and birth candidate metabolite biomarkers for fresh and vitrified IVP embryos in blood of beef cattle recipients. Our findings can help to improve embryo-recipient selection, which is usually carried out in a way that females that will not become pregnant are not well differentiated.
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Affiliation(s)
- Enrique Gómez
- Centro de Biotecnología Animal - SERIDA- Camino de Rioseco, 1225 Gijón, Spain.
| | - Marta Muñoz
- Centro de Biotecnología Animal - SERIDA- Camino de Rioseco, 1225 Gijón, Spain
| | - Julie Gatien
- ALLICE, Experimental facilities, Le Perroi, 37380 Nouzilly, France
| | - Susana Carrocera
- Centro de Biotecnología Animal - SERIDA- Camino de Rioseco, 1225 Gijón, Spain
| | | | - Pascal Salvetti
- ALLICE, Experimental facilities, Le Perroi, 37380 Nouzilly, France
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41
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Maternal plasma metabolic markers of neonatal adiposity and associated maternal characteristics: The GUSTO study. Sci Rep 2020; 10:9422. [PMID: 32523012 PMCID: PMC7287081 DOI: 10.1038/s41598-020-66026-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 05/12/2020] [Indexed: 11/23/2022] Open
Abstract
Infant adiposity may be related to later metabolic health. Maternal metabolite profiling reflects both genetic and environmental influences and allows elucidation of metabolic pathways associated with infant adiposity. In this multi-ethnic Asian cohort, we aimed to (i) identify maternal plasma metabolites associated with infant adiposity and other birth outcomes and (ii) investigate the maternal characteristics associated with those metabolites. In 940 mother-offspring pairs, we performed gas chromatography-mass spectrometry and identified 134 metabolites in maternal fasting plasma at 26–28 weeks of gestation. At birth, neonatal triceps and subscapular skinfold thicknesses were measured by trained research personnel, while weight and length measures were abstracted from delivery records. Gestational age was estimated from first-trimester dating ultrasound. Associations were assessed by multivariable linear regression, with p-values corrected using the Benjamini-Hochberg approach. At a false discovery rate of 5%, we observed associations between 28 metabolites and neonatal sum of skinfold thicknesses (13 amino acid-related, 4 non-esterified fatty acids, 6 xenobiotics, and 5 unknown compounds). Few associations were observed with gestational duration, birth weight, or birth length. Maternal ethnicity, pre-pregnancy BMI, and diet quality during pregnancy had the strongest associations with the specific metabolome related to infant adiposity. Further studies are warranted to replicate our findings and to understand the underlying mechanisms.
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Rohwerder T, Rohde MT, Jehmlich N, Purswani J. Actinobacterial Degradation of 2-Hydroxyisobutyric Acid Proceeds via Acetone and Formyl-CoA by Employing a Thiamine-Dependent Lyase Reaction. Front Microbiol 2020; 11:691. [PMID: 32351493 PMCID: PMC7176365 DOI: 10.3389/fmicb.2020.00691] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 03/25/2020] [Indexed: 11/13/2022] Open
Abstract
The tertiary branched short-chain 2-hydroxyisobutyric acid (2-HIBA) has been associated with several metabolic diseases and lysine 2-hydroxyisobutyrylation seems to be a common eukaryotic as well as prokaryotic post-translational modification in proteins. In contrast, the underlying 2-HIBA metabolism has thus far only been detected in a few microorganisms, such as the betaproteobacterium Aquincola tertiaricarbonis L108 and the Bacillus group bacterium Kyrpidia tusciae DSM 2912. In these strains, 2-HIBA can be specifically activated to the corresponding CoA thioester by the 2-HIBA-CoA ligase (HCL) and is then isomerized to 3-hydroxybutyryl-CoA in a reversible and B12-dependent mutase reaction. Here, we demonstrate that the actinobacterial strain Actinomycetospora chiangmaiensis DSM 45062 degrades 2-HIBA and also its precursor 2-methylpropane-1,2-diol via acetone and formic acid by employing a thiamine pyrophosphate-dependent lyase. The corresponding gene is located directly upstream of hcl, which has previously been found only in operonic association with the 2-hydroxyisobutyryl-CoA mutase genes in other bacteria. Heterologous expression of the lyase gene from DSM 45062 in E. coli established a 2-hydroxyisobutyryl-CoA lyase activity in the latter. In line with this, analysis of the DSM 45062 proteome reveals a strong induction of the lyase-HCL gene cluster on 2-HIBA. Acetone is likely degraded via hydroxylation to acetol catalyzed by a MimABCD-related binuclear iron monooxygenase and formic acid appears to be oxidized to CO2 by selenium-dependent dehydrogenases. The presence of the lyase-HCL gene cluster in isoprene-degrading Rhodococcus strains and Pseudonocardia associated with tropical leafcutter ant species points to a role in degradation of biogenic short-chain ketones and highly branched organic compounds.
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Affiliation(s)
- Thore Rohwerder
- Department of Environmental Microbiology, Helmholtz Centre for Environmental Research, Leipzig, Germany
| | - Maria-Teresa Rohde
- Institut für Chemie - Biophysikalische Chemie, Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Germany
| | - Nico Jehmlich
- Department of Molecular Systems Biology, Helmholtz Centre for Environmental Research, Leipzig, Germany
| | - Jessica Purswani
- Institute of Water Research, University of Granada, Granada, Spain
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Mack CI, Ferrario PG, Weinert CH, Egert B, Hoefle AS, Lee YM, Skurk T, Kulling SE, Daniel H. Exploring the Diversity of Sugar Compounds in Healthy, Prediabetic, and Diabetic Volunteers. Mol Nutr Food Res 2020; 64:e1901190. [PMID: 32170825 DOI: 10.1002/mnfr.201901190] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 01/31/2020] [Indexed: 01/10/2023]
Abstract
SCOPE Diabetes is thought to primarily represent a disturbance of carbohydrate metabolism; however, population studies employing metabolomics have mainly identified plasma amino acids and lipids, or their products, as biomarkers. In this pilot study, the aim is to analyze a wide spectrum of sugar compounds in the fasting state and during an oral glucose tolerance test (OGTT) in healthy, prediabetic, and type 2 diabetic volunteers. METHODS AND RESULTS The three volunteer groups underwent a standard OGTT. Plasma samples obtained in the fasting state, 30 and 90 min after the OGTT, are subjected to a semitargeted GC-MS (gas chromatography-mass spectrometry) sugar profiling. Overall, 40 sugars are detected in plasma, of which some are yet unknown to change during an OGTT. Several sugars (e.g., trehalose) reveal significant differences between the volunteer groups both in fasting plasma and in distinct time courses after the OGTT. This suggests an endogenous production from orally absorbed glucose and/or an insulin-dependent production/removal from plasma. CONCLUSION It is demonstrated that more sugars than expected can be found in human plasma. Since some of these show characteristic differences depending on health status, it may be worthwhile to assess their usability as biomarkers for diagnosing early-stage insulin resistance and type 2 diabetes.
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Affiliation(s)
- Carina I Mack
- Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Haid-und-Neu-Strasse 9, Karlsruhe, 76131, Germany
| | - Paola G Ferrario
- Department of Physiology and Biochemistry of Nutrition, Max Rubner-Institut, Haid-und-Neu-Strasse 9, Karlsruhe, 76131, Germany
| | - Christoph H Weinert
- Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Haid-und-Neu-Strasse 9, Karlsruhe, 76131, Germany
| | - Björn Egert
- Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Haid-und-Neu-Strasse 9, Karlsruhe, 76131, Germany
| | - Anja S Hoefle
- Department of Food and Nutrition, Technical University of Munich, Gregor-Mendel-Strasse 2, Freising-Weihenstephan, 85354, Germany
| | - Yu-Mi Lee
- Department of Food and Nutrition, Technical University of Munich, Gregor-Mendel-Strasse 2, Freising-Weihenstephan, 85354, Germany
| | - Thomas Skurk
- Core Facility Human Studies, ZIEL Institute for Food and Health, Technical University of Munich, Gregor-Mendel-Strasse 2, Freising-Weihenstephan, 85354, Germany.,Else Kröner-Fresenius-Center for Nutritional Medicine, Technical University of Munich, Gregor-Mendel-Strasse 2, Freising-Weihenstephan, 85354, Germany
| | - Sabine E Kulling
- Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Haid-und-Neu-Strasse 9, Karlsruhe, 76131, Germany
| | - Hannelore Daniel
- Department of Food and Nutrition, Technical University of Munich, Gregor-Mendel-Strasse 2, Freising-Weihenstephan, 85354, Germany
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Neul JL, Skinner SA, Annese F, Lane J, Heydemann P, Jones M, Kaufmann WE, Glaze DG, Percy AK. Metabolic Signatures Differentiate Rett Syndrome From Unaffected Siblings. Front Integr Neurosci 2020; 14:7. [PMID: 32161522 PMCID: PMC7052375 DOI: 10.3389/fnint.2020.00007] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Accepted: 01/30/2020] [Indexed: 01/07/2023] Open
Abstract
Rett syndrome (RTT, OMIM 312750), a severe neurodevelopmental disorder characterized by regression with loss of spoken language and hand skills, development of characteristic hand stereotypies, and gait dysfunction, is primarily caused by de novo mutations in the X-linked gene Methyl-CpG-binding protein 2 (MECP2). Currently, treatment options are limited to symptomatic management, however, reversal of disease phenotype is possible in mouse models by restoration of normal MECP2 gene expression. A significant challenge is the lack of biomarkers of disease state, disease severity, or treatment response. Using a non-targeted metabolomic approach we evaluated metabolite profiles in plasma from thirty-four people with RTT compared to thirty-seven unaffected age- and gender-matched siblings. We identified sixty-six significantly altered metabolites that cluster broadly into amino acid, nitrogen handling, and exogenous substance pathways. RTT disease metabolite and metabolic pathways abnormalities point to evidence of oxidative stress, mitochondrial dysfunction, and alterations in gut microflora. These observed changes provide insight into underlying pathological mechanisms and the foundation for biomarker discovery of disease severity biomarkers.
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Affiliation(s)
- Jeffrey L Neul
- Vanderbilt University Medical Center, Nashville, TN, United States.,Department of Neurosciences, University of California, San Diego, San Diego, CA, United States.,Baylor College of Medicine, Houston, TX, United States
| | | | - Fran Annese
- Greenwood Genetic Center, Greenwood, SC, United States
| | - Jane Lane
- Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL, United States
| | | | - Mary Jones
- Benioff Children's Hospital Oakland, University of California, San Francisco, San Francisco, CA, United States
| | | | | | - Alan K Percy
- Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL, United States
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Brial F, Alzaid F, Sonomura K, Kamatani Y, Meneyrol K, Le Lay A, Péan N, Hedjazi L, Sato TA, Venteclef N, Magnan C, Lathrop M, Dumas ME, Matsuda F, Zalloua P, Gauguier D. The Natural Metabolite 4-Cresol Improves Glucose Homeostasis and Enhances β-Cell Function. Cell Rep 2020; 30:2306-2320.e5. [PMID: 32075738 DOI: 10.1016/j.celrep.2020.01.066] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2019] [Revised: 10/26/2019] [Accepted: 01/22/2020] [Indexed: 02/09/2023] Open
Abstract
Exposure to natural metabolites contributes to the risk of cardiometabolic diseases (CMDs). Through metabolome profiling, we identify the inverse correlation between serum concentrations of 4-cresol and type 2 diabetes. The chronic administration of non-toxic doses of 4-cresol in complementary preclinical models of CMD reduces adiposity, glucose intolerance, and liver triglycerides, enhances insulin secretion in vivo, stimulates islet density and size, and pancreatic β-cell proliferation, and increases vascularization, suggesting activated islet enlargement. In vivo insulin sensitivity is not affected by 4-cresol. The incubation of mouse isolated islets with 4-cresol results in enhanced insulin secretion, insulin content, and β-cell proliferation of a magnitude similar to that induced by GLP-1. In both CMD models and isolated islets, 4-cresol is associated with the downregulated expression of the kinase DYRK1A, which may mediate its biological effects. Our findings identify 4-cresol as an effective regulator of β-cell function, which opens up perspectives for therapeutic applications in syndromes of insulin deficiency.
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Affiliation(s)
- Francois Brial
- Université de Paris, INSERM UMR 1124, 75006 Paris, France
| | - Fawaz Alzaid
- Sorbonne Université, Université Paris Descartes, INSERM UMR_S 1138, Cordeliers Research Centre, 75006 Paris, France
| | - Kazuhiro Sonomura
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8501, Japan; Life Science Research Center, Technology Research Laboratory, Shimadzu, Kyoto 604-8511, Japan
| | - Yoichiro Kamatani
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8501, Japan
| | - Kelly Meneyrol
- Université de Paris, Unit of Functional and Adaptive Biology, UMR 8251, CNRS, 4 rue Marie Andrée Lagroua Weill-Halle, 75013 Paris, France
| | - Aurélie Le Lay
- Université de Paris, INSERM UMR 1124, 75006 Paris, France
| | - Noémie Péan
- Université de Paris, INSERM UMR 1124, 75006 Paris, France
| | | | - Taka-Aki Sato
- Life Science Research Center, Technology Research Laboratory, Shimadzu, Kyoto 604-8511, Japan
| | - Nicolas Venteclef
- Sorbonne Université, Université Paris Descartes, INSERM UMR_S 1138, Cordeliers Research Centre, 75006 Paris, France
| | - Christophe Magnan
- Université de Paris, Unit of Functional and Adaptive Biology, UMR 8251, CNRS, 4 rue Marie Andrée Lagroua Weill-Halle, 75013 Paris, France
| | - Mark Lathrop
- McGill University and Genome Quebec Innovation Centre, 740 Doctor Penfield Avenue, Montreal, QC H3A 0G1, Canada
| | - Marc-Emmanuel Dumas
- Imperial College London, Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Sir Alexander Fleming Building, London SW7 2AZ, UK
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8501, Japan
| | - Pierre Zalloua
- Lebanese American University, School of Medicine, Beirut 1102 2801, Lebanon.
| | - Dominique Gauguier
- Université de Paris, INSERM UMR 1124, 75006 Paris, France; Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8501, Japan; McGill University and Genome Quebec Innovation Centre, 740 Doctor Penfield Avenue, Montreal, QC H3A 0G1, Canada.
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46
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Mommers J, van der Wal S. Column Selection and Optimization for Comprehensive Two-Dimensional Gas Chromatography: A Review. Crit Rev Anal Chem 2020; 51:183-202. [DOI: 10.1080/10408347.2019.1707643] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- John Mommers
- DSM Material Science Center, Geleen, The Netherlands
| | - Sjoerd van der Wal
- Polymer-Analysis Group, University of Amsterdam, Amsterdam, The Netherlands
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47
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48
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Di Giovanni N, Meuwis MA, Louis E, Focant JF. Untargeted Serum Metabolic Profiling by Comprehensive Two-Dimensional Gas Chromatography–High-Resolution Time-of-Flight Mass Spectrometry. J Proteome Res 2019; 19:1013-1028. [DOI: 10.1021/acs.jproteome.9b00535] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Nicolas Di Giovanni
- Department of Chemistry, Organic and Biological Analytical Chemistry Group, Quartier Agora, University of Liège, Allée du Six Août, B6c, B-4000 Liège (Sart Tilman), Belgium
| | - Marie-Alice Meuwis
- GIGA institute, Translational Gastroenterology and CHU de Liège, Hepato-Gastroenterology and Digestive Oncology, Quartier Hôpital, University of Liège, Avenue de l’Hôpital 13, B34-35, B-4000 Liège, Belgium
| | - Edouard Louis
- GIGA institute, Translational Gastroenterology and CHU de Liège, Hepato-Gastroenterology and Digestive Oncology, Quartier Hôpital, University of Liège, Avenue de l’Hôpital 13, B34-35, B-4000 Liège, Belgium
| | - Jean-François Focant
- Department of Chemistry, Organic and Biological Analytical Chemistry Group, Quartier Agora, University of Liège, Allée du Six Août, B6c, B-4000 Liège (Sart Tilman), Belgium
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49
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Serum metabolomics profiling and potential biomarkers of myopia using LC-QTOF/MS. Exp Eye Res 2019; 186:107737. [DOI: 10.1016/j.exer.2019.107737] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 07/15/2019] [Accepted: 07/16/2019] [Indexed: 12/25/2022]
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50
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Zhuang Y, Xing C, Cao H, Zhang C, Luo J, Guo X, Hu G. Insulin resistance and metabonomics analysis of fatty liver haemorrhagic syndrome in laying hens induced by a high-energy low-protein diet. Sci Rep 2019; 9:10141. [PMID: 31300671 PMCID: PMC6626135 DOI: 10.1038/s41598-019-46183-y] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 06/24/2019] [Indexed: 12/31/2022] Open
Abstract
Fatty liver haemorrhagic syndrome (FLHS) is a widespread metabolic disease in laying hens that causes a decrease in egg production and even death. Insulin resistance is a major contributor to the pathogenesis of nonalcoholic fatty liver disease. However, the relationship between FLHS and the insulin resistance mechanisms underlying FLHS is not well elucidated. Therefore, we established an FLHS model induced by feeding a high-energy low-protein diet. In the current study, we found that the fasting glucose and insulin concentrations were elevated in the FLHS group compared with the control group during the experimental period. The results of the oral glucose tolerance test (OGTT) and insulin sensitivity test (IST) showed a high level of insulin resistance in the FLHS model. InsR, 4EBP-1, Glut-1 and Glut-3 mRNA expression were decreased, and TOR, S6K1, and FOXO1 were elevated (P < 0.05). Metabolomic analysis with GC/MS identified 46 differentially expressed metabolites between these two groups, and of these, 14 kinds of metabolism molecules and 32 kinds of small metabolism molecules were decreased (P < 0.05). Further investigation showed that glucose, lipid and amino acid metabolism blocks in the progression of FLHS by GO functional and pathway analysis. Overall, these results suggest that insulin resistance participated in FLHS; comprehensively, metabolites participated in the dysregulated biological process.
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Affiliation(s)
- Yu Zhuang
- Jiangxi Provincial Key Laboratory for Animal Health, Institute of Animal Population Health, College of Animal Science and Technology, Jiangxi Agricultural University, No. 1101 Zhimin Avenue, Economic and Technological Development District, Nanchang, 330045, Jiangxi, P.R. China
| | - Chenghong Xing
- Jiangxi Provincial Key Laboratory for Animal Health, Institute of Animal Population Health, College of Animal Science and Technology, Jiangxi Agricultural University, No. 1101 Zhimin Avenue, Economic and Technological Development District, Nanchang, 330045, Jiangxi, P.R. China
| | - Huabin Cao
- Jiangxi Provincial Key Laboratory for Animal Health, Institute of Animal Population Health, College of Animal Science and Technology, Jiangxi Agricultural University, No. 1101 Zhimin Avenue, Economic and Technological Development District, Nanchang, 330045, Jiangxi, P.R. China
| | - Caiying Zhang
- Jiangxi Provincial Key Laboratory for Animal Health, Institute of Animal Population Health, College of Animal Science and Technology, Jiangxi Agricultural University, No. 1101 Zhimin Avenue, Economic and Technological Development District, Nanchang, 330045, Jiangxi, P.R. China
| | - Junrong Luo
- Jiangxi Provincial Key Laboratory for Animal Health, Institute of Animal Population Health, College of Animal Science and Technology, Jiangxi Agricultural University, No. 1101 Zhimin Avenue, Economic and Technological Development District, Nanchang, 330045, Jiangxi, P.R. China
| | - Xiaoquan Guo
- Jiangxi Provincial Key Laboratory for Animal Health, Institute of Animal Population Health, College of Animal Science and Technology, Jiangxi Agricultural University, No. 1101 Zhimin Avenue, Economic and Technological Development District, Nanchang, 330045, Jiangxi, P.R. China
| | - Guoliang Hu
- Jiangxi Provincial Key Laboratory for Animal Health, Institute of Animal Population Health, College of Animal Science and Technology, Jiangxi Agricultural University, No. 1101 Zhimin Avenue, Economic and Technological Development District, Nanchang, 330045, Jiangxi, P.R. China.
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