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Hubert DL, Arnold KR, Greenspan ZG, Pupo A, Robinson RD, Chavarin VV, Barter TB, Djukovic D, Raftery D, Vue Z, Hinton A, McReynolds MR, Harrison BR, Phillips MA. Selection for early reproduction leads to accelerated aging and extensive metabolic remodeling in Drosophila melanogaster populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.28.601037. [PMID: 39005259 PMCID: PMC11244849 DOI: 10.1101/2024.06.28.601037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Experimental evolution studies that feature selection on life-history characters are a proven approach for studying the evolution of aging and variation in rates of senescence. Recently, the incorporation of genomic and transcriptomic approaches into this framework has led to the identification of hundreds of genes associated with different aging patterns. However, our understanding of the specific molecular mechanisms underlying these aging patterns remains limited. Here, we incorporated extensive metabolomic profiling into this framework to generate mechanistic insights into aging patterns in Drosophila melanogaster . Specifically, we characterized metabolomic change over time associated with accelerated aging in populations of D. melanogaster under selection for early reproduction compared to their controls. Using this data we: i) evaluated the evolutionary repeatability across the metabolome; ii) evaluated the value of the metabolome as a predictor of "biological age" in this system; and iii) identified specific metabolic pathways associated with accelerated aging. Generally, our findings suggest that the metabolome is a reliable predictor of age and senescence in populations that share a recent evolutionary history. Metabolomic analysis revealed that generations of selection for early reproduction resulted in highly repeatable alterations to the metabolome. Specifically, changes in carbohydrate, amino acid, and TCA cycle-related metabolite abundances over time point to metabolic remodeling that favors rapid early reproduction with long-term consequences for carbohydrate and protein utilization.
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Yang SH, Kim YJ, Yang HR, Park SU, Kim JG, Kim JK. Metabolic Profiling in Plasma and Brain Induced by 17β-Estradiol Supplementation in Ovariectomized Mice. ACS OMEGA 2024; 9:18212-18223. [PMID: 38680363 PMCID: PMC11044158 DOI: 10.1021/acsomega.3c10399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 03/25/2024] [Accepted: 03/27/2024] [Indexed: 05/01/2024]
Abstract
17β-Estradiol is an ovarian hormone that regulates energy circulation and storage by acting on the central nervous system. However, the metabolic differences between the blood and brain when stimulated by 17β-estradiol are poorly understood. Moreover, research using menopause-induced models to investigate primary metabolites in the blood and brain is limited. Thus, this study aimed to identify metabolic changes in the plasma and brain resulting from 17β-estradiol supplementation in an estrogen-deficient mouse model. Three groups of mice were utilized: sham-operated mice (Sham), ovariectomized mice (OVX), and ovariectomized mice that received a weekly supplementation of 17β-estradiol (E2). Plasma and brain samples from these mice were subjected to metabolic analysis using gas chromatography-time-of-flight-mass spectrometry. Compared with the plasma samples from the Sham and OVX groups, the plasma samples from the E2 group contained higher contents of branched-chain amino acids (BCAAs), such as valine, isoleucine, and leucine. Meanwhile, the brain samples from the E2 group contained higher contents of most metabolites, including BCAAs, neurotransmitters, tricarboxylic acid cycle intermediates, and fatty acids, than those from the two other groups. This study is the first to reveal differences in energy metabolism induced by 17β-estradiol supplementation through brain metabolic profiling of ovariectomized mice, emphasizing the importance of brain metabolic profiling in menopausal hormone research.
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Affiliation(s)
- So Hwi Yang
- Division
of Life Sciences, College of Life Sciences, and Bioengineering, Incheon National University, Incheon 22012, Republic of Korea
| | - Ye Jin Kim
- Division
of Life Sciences, College of Life Sciences, and Bioengineering, Incheon National University, Incheon 22012, Republic of Korea
| | - Hye Rim Yang
- Division
of Life Sciences, College of Life Sciences, and Bioengineering, Incheon National University, Incheon 22012, Republic of Korea
| | - Sang Un Park
- Department
of Crop Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Republic of Korea
| | - Jae Geun Kim
- Division
of Life Sciences, College of Life Sciences, and Bioengineering, Incheon National University, Incheon 22012, Republic of Korea
| | - Jae Kwang Kim
- Division
of Life Sciences, College of Life Sciences, and Bioengineering, Incheon National University, Incheon 22012, Republic of Korea
- Convergence
Research Center for Insect Vectors, Incheon
National University, Incheon 22012, Republic
of Korea
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Tao H, Zhou L, Yu D, Chen Y, Luo Y, Lin T. Effects of polystyrene microplastics on the metabolic level of Pseudomonas aeruginosa. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 922:171335. [PMID: 38423332 DOI: 10.1016/j.scitotenv.2024.171335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 02/22/2024] [Accepted: 02/26/2024] [Indexed: 03/02/2024]
Abstract
Given the widespread presence of Pseudomonas aeruginosa in water and its threat to human health, the metabolic changes in Pseudomonas aeruginosa when exposed to polystyrene microplastics (PS-MPs) exposure were studied, focusing on molecular level. Through non-targeted metabolomics, a total of 64 differential metabolites were screened out under positive ion mode and 44 under negative ion mode. The content of bacterial metabolites changed significantly, primarily involving lipids, nucleotides, amino acids, and organic acids. Heightened intracellular oxidative damage led to a decrease in lipid molecules and nucleotide-related metabolites. The down-regulation of amino acid metabolites, such as L-Glutamic and L-Proline, highlighted disruptions in cellular energy metabolism and the impaired ability to synthesize proteins as a defense against oxidation. The impact of PS-MPs on organic acid metabolism was evident in the inhibition of pyruvate and citrate, thereby disrupting the cells' normal participation in energy cycles. The integration of Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that PS-MPs mainly caused changes in metabolic pathways, including ABC transporters, Aminoacyl-tRNA biosynthesis, Purine metabolism, Glycerophospholipid metabolism and TCA cycle in Pseudomonas aeruginosa. Most of the differential metabolites enriched in these pathways were down-regulated, demonstrating that PS-MPs hindered the expression of metabolic pathways, ultimately impairing the ability of cells to synthesize proteins, DNA, and RNA. This disruption affected cell proliferation and information transduction, thus hampering energy circulation and inhibiting cell growth. Findings of this study supplemented the toxic effects of microplastics and the defense mechanisms of microorganisms, in turn safeguarding drinking water safety and human health.
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Affiliation(s)
- Hui Tao
- Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, PR China; College of Environment, Hohai University, Nanjing 210098, PR China.
| | - Lingqin Zhou
- Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, PR China; College of Environment, Hohai University, Nanjing 210098, PR China
| | - Duo Yu
- Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, PR China; College of Environment, Hohai University, Nanjing 210098, PR China
| | - Yiyang Chen
- Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, PR China; College of Environment, Hohai University, Nanjing 210098, PR China
| | - Yunxin Luo
- Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, PR China; College of Environment, Hohai University, Nanjing 210098, PR China
| | - Tao Lin
- Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, PR China; College of Environment, Hohai University, Nanjing 210098, PR China
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Manickavasagam G, Saaid M, Lim V. Exploring stingless bee honey from selected regions of Peninsular Malaysia through gas chromatography-mass spectrometry-based untargeted metabolomics. J Food Sci 2024; 89:1058-1072. [PMID: 38221804 DOI: 10.1111/1750-3841.16903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 12/02/2023] [Accepted: 12/10/2023] [Indexed: 01/16/2024]
Abstract
Volatile organic compounds in honey are known for their considerable impact on the organoleptic properties of honey, such as aroma, flavor, taste, and texture. The type and composition of volatile organic compounds are influenced by entomological, geographical, and botanical origins; thus, these compounds have the potential to be chemical markers. Sixty-two volatile compounds were identified using gas chromatography-mass spectrometry from 30 Heterotrigona itama (H. itama) honey samples from 3 different geographical origins. Hydrocarbons and benzene derivatives were the dominant classes of volatile organic compounds in the samples. Both clustering and discriminant analyses demonstrated a clear separation between samples from distant origins (Kedah and Perak), and the volcano plot supported it. The reliability and predictability of the partial least squares-discriminant analysis model from the discriminant analysis were validated using cross-validation (R2 : 0.93; Q2 : 0.83; accuracy: 0.97) and the permutation test (p < 0.001), and the output depicted that the model is legitimate. In combination with the variable importance of projection (VIP > 1.0) and the Kruskal-Wallis test (p < 0.01), 19 volatile organic compounds (encompassed aldehydes, benzene derivatives, esters, hydrocarbons, and terpenoids) were sorted and named potent chemical markers in classifying honey samples from three geographical origins. In brief, this study illustrated that volatile organic compounds of stingless honey originated from the same bee species, but different geographical origins could be applied as chemical markers.
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Affiliation(s)
| | - Mardiana Saaid
- School of Chemical Sciences, Universiti Sains Malaysia, Gelugor, Pulau Pinang, Malaysia
| | - Vuanghao Lim
- Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, Kepala Batas, Pulau Pinang, Malaysia
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Chardin D, Jing L, Chazal-Ngo-Mai M, Guigonis JM, Rigau V, Goze C, Duffau H, Virolle T, Pourcher T, Burel-Vandenbos F. Identification of Metabolomic Markers in Frozen or Formalin-Fixed and Paraffin-Embedded Samples of Diffuse Glioma from Adults. Int J Mol Sci 2023; 24:16697. [PMID: 38069019 PMCID: PMC10705927 DOI: 10.3390/ijms242316697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 11/17/2023] [Accepted: 11/21/2023] [Indexed: 12/18/2023] Open
Abstract
The aim of this study was to identify metabolomic signatures associated with the gliomagenesis pathway (IDH-mutant or IDH-wt) and tumor grade of diffuse gliomas (DGs) according to the 2021 WHO classification on frozen samples and to evaluate the diagnostic performances of these signatures in tumor samples that are formalin-fixed and paraffin-embedded (FFPE). An untargeted metabolomic study was performed using liquid chromatography/mass spectrometry on a cohort of 213 DG samples. Logistic regression with LASSO penalization was used on the frozen samples to build classification models in order to identify IDH-mutant vs. IDH-wildtype DG and high-grade vs low-grade DG samples. 2-Hydroxyglutarate (2HG) was a metabolite of interest to predict IDH mutational status and aminoadipic acid (AAA) and guanidinoacetic acid (GAA) were significantly associated with grade. The diagnostic performances of the models were 82.6% AUC, 70.6% sensitivity and 80.4% specificity for 2HG to predict IDH status and 84.7% AUC, 78.1% sensitivity and 73.4% specificity for AAA and GAA to predict grade from FFPE samples. Thus, this study showed that AAA and GAA are two novel metabolites of interest in DG and that metabolomic data can be useful in the classification of DG, both in frozen and FFPE samples.
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Affiliation(s)
- David Chardin
- Laboratory Transporter in Imaging and Radiotherapy in Oncology (TIRO), Direction de la Recherche Fondamentale (DRF), Institut des Sciences du Vivant Frederic Joliot, Commissariat a l’Energie Atomique et aux Energies Alternatives (CEA), Université Cote d’Azur (UCA), 06000 Nice, France; (D.C.); (L.J.); (J.-M.G.); (T.P.)
- Service de Médecine Nucléaire, Centre Antoine Lacassagne, Université Cote d’Azur, 06000 Nice, France
| | - Lun Jing
- Laboratory Transporter in Imaging and Radiotherapy in Oncology (TIRO), Direction de la Recherche Fondamentale (DRF), Institut des Sciences du Vivant Frederic Joliot, Commissariat a l’Energie Atomique et aux Energies Alternatives (CEA), Université Cote d’Azur (UCA), 06000 Nice, France; (D.C.); (L.J.); (J.-M.G.); (T.P.)
| | | | - Jean-Marie Guigonis
- Laboratory Transporter in Imaging and Radiotherapy in Oncology (TIRO), Direction de la Recherche Fondamentale (DRF), Institut des Sciences du Vivant Frederic Joliot, Commissariat a l’Energie Atomique et aux Energies Alternatives (CEA), Université Cote d’Azur (UCA), 06000 Nice, France; (D.C.); (L.J.); (J.-M.G.); (T.P.)
| | - Valérie Rigau
- Department of Pathology and Oncobiology, Institute for Neurosciences of Montpellier, INSERM U1051, University Hospital of Montpellier, 34000 Montpellier, France;
| | - Catherine Goze
- Laboratory of Solid Tumors Biology, Institute for Neurosciences of Montpellier, INSERM U1051, University Hospital of Montpellier, 34000 Montpellier, France;
| | - Hugues Duffau
- Neurosurgery Department, Institute for Neurosciences of Montpellier, INSERM U1051, University Hospital of Montpellier, 34000 Montpellier, France;
| | - Thierry Virolle
- Team INSERM “Cancer Stem Cell Plasticity and Functional Intra-Tumor Heterogeneity”, Institut de Biologie Valrose, Université Côte D’Azur, CNRS, INSERM, 06000 Nice, France;
| | - Thierry Pourcher
- Laboratory Transporter in Imaging and Radiotherapy in Oncology (TIRO), Direction de la Recherche Fondamentale (DRF), Institut des Sciences du Vivant Frederic Joliot, Commissariat a l’Energie Atomique et aux Energies Alternatives (CEA), Université Cote d’Azur (UCA), 06000 Nice, France; (D.C.); (L.J.); (J.-M.G.); (T.P.)
| | - Fanny Burel-Vandenbos
- Department of Pathology, University Hospital of Nice, 06000 Nice, France;
- Laboratory “Cancer Stem Cell Plasticity and Functional Intra-Tumor Heterogeneity”, UMR CNRS 7277-UMR INSERM 1091, Institute of Biology Valrose, University Côte d’Azur, 06000 Nice, France
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Vannabhum M, Mahajaroensiri S, Pattanapholkornsakul S, Tantiwongsekunakorn A, Thippayacharoentam T, Tripatara P, Akarasereenont P. Metabolomics of Personalized Body Elements in Thai Traditional Medicine Response to Herbal Medicine for Body Elements Balancing in Healthy Volunteers. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE : ECAM 2023; 2023:6684263. [PMID: 37954926 PMCID: PMC10640159 DOI: 10.1155/2023/6684263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 09/05/2023] [Accepted: 10/25/2023] [Indexed: 11/14/2023]
Abstract
Background In Thai traditional medicine (TTM), the dominant body element called "Dhat Chao Ruean" (DCR) is an integral part in the diagnostic process of Thai traditional medicine. TTM practitioners usually use Thai herbal Benjakul formula (BKF) for adjusting and balancing the body elements. However, the effects of BKF on metabolism and individual response to it have not been studied yet. Methods This study proposed to investigate the metabolic profiling in 24 volunteers categorized by their types of birth month DCR (bDCR) after the administration of BKF (450 mg, three tablets three times a day before meals) for seven days. Differences in metabolic profiling between bDCR groups were investigated by using liquid chromatography coupled with mass spectrometry for untargeted analysis, and in addition, the safety was assessed by testing the plasma biochemical level. Results This study identified 57 biomarkers in positive ESI and 12 in negative ESI. Piperine was found in varying amount among the participants but it was the highest in the earth group. In addition, this study found that elemicin, phenylpropionic acid, ricinoleic acid, and β-sitosterol are important substances in a single herb of BKF. Regarding biochemical tests, the results indicated that BKF can decrease the lipid profile and it has no toxic effects on liver and kidney functions. Conclusion The findings indicated that it is safe to use BKF which can help to improve health in chronic diseases by adjusting abnormality of the elements of the body. In addition, the information gathered from this study is valuable for further study in the field of Thai traditional medicine.
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Affiliation(s)
- Manmas Vannabhum
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Suthatip Mahajaroensiri
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Saracha Pattanapholkornsakul
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Athippat Tantiwongsekunakorn
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Thapthep Thippayacharoentam
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Pinpat Tripatara
- Pharmacology Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Pravit Akarasereenont
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Pharmacology Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
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Huang D, Yang Y, Song W, Jiang C, Zhang Y, Zhang A, Lin Z, Ke X. Untargeted metabonomic analysis of a cerebral stroke model in rats: a study based on UPLC-MS/MS. Front Neurosci 2023; 17:1084813. [PMID: 37614341 PMCID: PMC10442664 DOI: 10.3389/fnins.2023.1084813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 07/18/2023] [Indexed: 08/25/2023] Open
Abstract
Introduction Brain tissue damage caused by ischemic stroke can trigger changes in the body's metabolic response, and understanding the changes in the metabolic response of the gut after stroke can contribute to research on poststroke brain function recovery. Despite the increase in international research on poststroke metabolic mechanisms and the availability of powerful research tools in recent years, there is still an urgent need for poststroke metabolic studies. Metabolomic examination of feces from a cerebral ischemia-reperfusion rat model can provide new insights into poststroke metabolism and identify key metabolic pathways, which will help reveal diagnostic and therapeutic targets as well as inspire pathophysiological studies after stroke. Methods We randomly divided 16 healthy adult pathogen-free male Sprague-Dawley (SD) rats into the normal group and the study group, which received middle cerebral artery occlusion/reperfusion (MCAO/R). Ultra-performance liquid chromatography-tandem mass spectrometry (UPLCMS/MS) was used to determine the identities and concentrations of metabolites across all groups, and filtered high-quality data were analyzed for differential screening and differential metabolite functional analysis. Results After 1 and 14 days of modeling, compared to the normal group, rats in the study group showed significant neurological deficits (p < 0.001) and significantly increased infarct volume (day 1: p < 0.001; day 14: p = 0.001). Mass spectra identified 1,044 and 635 differential metabolites in rat feces in positive and negative ion modes, respectively, which differed significantly between the normal and study groups. The metabolites with increased levels identified in the study group were involved in tryptophan metabolism (p = 0.036678, p < 0.05), arachidonic acid metabolism (p = 0.15695), cysteine and methionine metabolism (p = 0.24705), and pyrimidine metabolism (p = 0.3413), whereas the metabolites with decreased levels were involved in arginine and proline metabolism (p = 0.15695) and starch and sucrose metabolism (p = 0.52256). Discussion We determined that UPLC-MS/MS could be employed for untargeted metabolomics research. Moreover, tryptophan metabolic pathways may have been disordered in the study group. Alterations in the tryptophan metabolome may provide additional theoretical and data support for elucidating stroke pathogenesis and selecting pathways for intervention.
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Affiliation(s)
- Dunbing Huang
- Department of Rehabilitation Medicine, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yihan Yang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Wei Song
- Department of Rehabilitation Medicine, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Cai Jiang
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
- Second Rehabilitation Department, Fujian Provincial Hospital, Fuzhou, China
- Fujian Provincial Center for Geriatrics, Fujian Provincial Hospital, Fuzhou, China
- Fujian Key Laboratory of Geriatrics Diseases, Fujian Provincial Hospital, Fuzhou, China
- Department of Complementary Medicine, University of Johannesburg, Johannesburg, South Africa
| | - Yuhao Zhang
- Department of Rehabilitation Medicine, Nanjing Lishui District Hospital of Traditional Chinese medicine, Nanjing, China
| | - Anren Zhang
- Department of Rehabilitation Medicine, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Zhonghua Lin
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
- Second Rehabilitation Department, Fujian Provincial Hospital, Fuzhou, China
- Fujian Provincial Center for Geriatrics, Fujian Provincial Hospital, Fuzhou, China
- Fujian Key Laboratory of Geriatrics Diseases, Fujian Provincial Hospital, Fuzhou, China
- Department of Complementary Medicine, University of Johannesburg, Johannesburg, South Africa
| | - Xiaohua Ke
- Department of Rehabilitation Medicine, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
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Yao S, Sapkota D, Hungerford JA, Kersten RD. Jujube Fruit Metabolomic Profiles Reveal Cultivar Differences and Function as Cultivar Fingerprints. PLANTS (BASEL, SWITZERLAND) 2023; 12:2313. [PMID: 37375938 DOI: 10.3390/plants12122313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 06/08/2023] [Accepted: 06/09/2023] [Indexed: 06/29/2023]
Abstract
Jujube is a nutritious fruit, and is high in vitamin C, fiber, phenolics, flavonoids, nucleotides, and organic acids. It is both an important food and a source of traditional medicine. Metabolomics can reveal metabolic differences between Ziziphus jujuba fruits from different jujube cultivars and growth sites. In the fall of 2022, mature fresh fruit of eleven cultivars from replicated trials at three sites in New Mexico-Leyendecker, Los Lunas, and Alcalde-were sampled from September to October for an untargeted metabolomics study. The 11 cultivars were Alcalde 1, Dongzao, Jinsi (JS), Jinkuiwang (JKW), Jixin, Kongfucui (KFC), Lang, Li, Maya, Shanxi Li, and Zaocuiwang (ZCW). Based on the LC-MS/MS analysis, there were 1315 compounds detected with amino acids and derivatives (20.15%) and flavonoids (15.44%) as dominant categories. The results reveal that the cultivar was the dominant factor in metabolite profiles, while the location was secondary. A pairwise comparison of cultivar metabolomes revealed that two pairs had fewer differential metabolites (i.e., Li/Shanxi Li and JS/JKW) than all the other pairs, highlighting that pairwise metabolic comparison can be applied for cultivar fingerprinting. Differential metabolite analysis also showed that half of drying cultivars have up-regulated lipid metabolites compared to fresh or multi-purpose fruit cultivars and that specialized metabolites vary significantly between cultivars from 35.3% (Dongzao/ZCW) to 56.7% (Jixin/KFC). An exemplary analyte matching sedative cyclopeptide alkaloid sanjoinine A was only detected in the Jinsi and Jinkuiwang cultivars. Overall, our metabolic analysis of the jujube cultivar's mature fruits provides the largest resource of jujube fruit metabolomes to date and will inform cultivar selection for nutritional and medicinal research and for fruit metabolic breeding.
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Affiliation(s)
- Shengrui Yao
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM 88003, USA
- Sustainable Agriculture Sciences Center, New Mexico State University, Alcalde, NM 87511, USA
| | - Dikshya Sapkota
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM 88003, USA
| | - Jordan A Hungerford
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, MI 48109, USA
| | - Roland D Kersten
- Department of Medicinal Chemistry, College of Pharmacy, University of Michigan, Ann Arbor, MI 48109, USA
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Decoding Metabolic Reprogramming in Plants under Pathogen Attacks, a Comprehensive Review of Emerging Metabolomics Technologies to Maximize Their Applications. Metabolites 2023; 13:metabo13030424. [PMID: 36984864 PMCID: PMC10055942 DOI: 10.3390/metabo13030424] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 03/01/2023] [Accepted: 03/09/2023] [Indexed: 03/15/2023] Open
Abstract
In their environment, plants interact with a multitude of living organisms and have to cope with a large variety of aggressions of biotic or abiotic origin. What has been known for several decades is that the extraordinary variety of chemical compounds the plants are capable of synthesizing may be estimated in the range of hundreds of thousands, but only a fraction has been fully characterized to be implicated in defense responses. Despite the vast importance of these metabolites for plants and also for human health, our knowledge about their biosynthetic pathways and functions is still fragmentary. Recent progress has been made particularly for the phenylpropanoids and oxylipids metabolism, which is more emphasized in this review. With an increasing interest in monitoring plant metabolic reprogramming, the development of advanced analysis methods should now follow. This review capitalizes on the advanced technologies used in metabolome mapping in planta, including different metabolomics approaches, imaging, flux analysis, and interpretation using bioinformatics tools. Advantages and limitations with regards to the application of each technique towards monitoring which metabolite class or type are highlighted, with special emphasis on the necessary future developments to better mirror such intricate metabolic interactions in planta.
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Widely Targeted Metabolomics Reveals Metabolite Diversity in Jalapeño and Serrano Chile Peppers ( Capsicum annuum L.). Metabolites 2023; 13:metabo13020288. [PMID: 36837906 PMCID: PMC9967468 DOI: 10.3390/metabo13020288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 02/12/2023] [Accepted: 02/13/2023] [Indexed: 02/18/2023] Open
Abstract
Chile peppers (Capsicum annuum L.) are good sources of vitamins and minerals that can be included in the diet to mitigate nutritional deficiencies. Metabolomics examines the metabolites involved in biological pathways to understand the genes related to complex phenotypes such as the nutritional quality traits. The current study surveys the different metabolites present in jalapeño ('NuMex Pumpkin Spice') and serrano ('NuMex LotaLutein') type chile peppers grown in New Mexico using a widely targeted metabolomics approach, with the 'NuMex LotaLutein' as control. A total of 1088 different metabolites were detected, where 345 metabolites were differentially expressed; 203 (59%) were downregulated and 142 (41%) were upregulated (i.e., relative metabolite content is higher in 'NuMex Pumpkin Spice'). The upregulated metabolites comprised mostly of phenolic acids (42), flavonoids (22), and organic acids (13). Analyses of principal component (PC) and orthogonal partial least squares demonstrated clustering based on cultivars, where at least 60% of variation was attributed to the first two PCs. Pathway annotation identified 89 metabolites which are involved in metabolic pathways and the biosynthesis of secondary metabolites. Altogether, metabolomics provided insights into the different metabolites present which can be targeted for breeding and selection towards the improvement of nutritional quality traits in Capsicum.
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Xia M, Valverde‐Barrantes OJ, Suseela V, Blackwood CB, Tharayil N. Characterizing natural variability of lignin abundance and composition in fine roots across temperate trees: a comparison of analytical methods. THE NEW PHYTOLOGIST 2022; 236:2358-2373. [PMID: 36168143 PMCID: PMC9828118 DOI: 10.1111/nph.18515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 08/27/2022] [Indexed: 06/16/2023]
Abstract
Lignin is an important root chemical component that is widely used in biogeochemical models to predict root decomposition. Across ecological studies, lignin abundance has been characterized using both proximate and lignin-specific methods, without much understanding of their comparability. This uncertainty in estimating lignin limits our ability to comprehend the mechanisms regulating root decomposition and to integrate lignin data for large-scale syntheses. We compared five methods of estimating lignin abundance and composition in fine roots across 34 phylogenetically diverse tree species. We also assessed the feasibility of high-throughput techniques for fast-screening of root lignin. Although acid-insoluble fraction (AIF) has been used to infer root lignin and decomposition, AIF-defined lignin content was disconnected from the lignin abundance estimated by techniques that specifically measure lignin-derived monomers. While lignin-specific techniques indicated lignin contents of 2-10% (w/w) in roots, AIF-defined lignin contents were c. 5-10-fold higher, and their interspecific variation was found to be largely unrelated to that determined using lignin-specific techniques. High-throughput pyrolysis-gas chromatography-mass spectrometry, when combined with quantitative modeling, accurately predicted lignin abundance and composition, highlighting its feasibility for quicker assessment of lignin in roots. We demonstrate that AIF should be interpreted separately from lignin in fine roots as its abundance is unrelated to that of lignin polymers. This study provides the basis for informed decision-making with respect to lignin methodology in ecology.
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Affiliation(s)
- Mengxue Xia
- Department of Plant & Environmental SciencesClemson UniversityClemsonSC29634USA
| | - Oscar J. Valverde‐Barrantes
- International Center for Tropical Biodiversity, Institute of EnvironmentFlorida International UniversityMiamiFL33199USA
| | - Vidya Suseela
- Department of Plant & Environmental SciencesClemson UniversityClemsonSC29634USA
| | | | - Nishanth Tharayil
- Department of Plant & Environmental SciencesClemson UniversityClemsonSC29634USA
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12
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Zhu Q, Qin M, Wang Z, Wu Y, Chen X, Liu C, Ma Q, Liu Y, Lai W, Chen H, Cai J, Liu Y, Lei F, Zhang B, Zhang S, He G, Li H, Zhang M, Zheng H, Chen J, Huang M, Zhong S. Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease. Cell Biosci 2022; 12:173. [PMID: 36242008 PMCID: PMC9569076 DOI: 10.1186/s13578-022-00863-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 07/28/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Coronary artery disease (CAD) is a metabolically perturbed pathological condition. However, the knowledge of metabolic signatures on outcomes of CAD and their potential causal effects and impacts on left ventricular remodeling remains limited. We aim to assess the contribution of plasma metabolites to the risk of death and major adverse cardiovascular events (MACE) as well as left ventricular remodeling. RESULTS In a prospective study with 1606 Chinese patients with CAD, we have identified and validated several independent metabolic signatures through widely-targeted metabolomics. The predictive model respectively integrating four metabolic signatures (dulcitol, β-pseudouridine, 3,3',5-Triiodo-L-thyronine, and kynurenine) for death (AUC of 83.7% vs. 76.6%, positive IDI of 0.096) and metabolic signatures (kynurenine, lysoPC 20:2, 5-methyluridine, and L-tryptophan) for MACE (AUC of 67.4% vs. 59.8%, IDI of 0.068) yielded better predictive value than trimethylamine N-oxide plus clinical model, which were successfully applied to predict patients with high risks of death (P = 0.0014) and MACE (P = 0.0008) in the multicenter validation cohort. Mendelian randomisation analysis showed that 11 genetically inferred metabolic signatures were significantly associated with risks of death or MACE, such as 4-acetamidobutyric acid, phenylacetyl-L-glutamine, tryptophan metabolites (kynurenine, kynurenic acid), and modified nucleosides (β-pseudouridine, 2-(dimethylamino) guanosine). Mediation analyses show that the association of these metabolites with the outcomes could be partly explained by their roles in promoting left ventricular dysfunction. CONCLUSIONS This study provided new insights into the relationship between plasma metabolites and clinical outcomes and its intermediate pathological process left ventricular dysfunction in CAD. The predictive model integrating metabolites can help to improve the risk stratification for death and MACE in CAD. The metabolic signatures appear to increase death or MACE risks partly by promoting adverse left ventricular dysfunction, supporting potential therapeutic targets of CAD for further investigation.
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Affiliation(s)
- Qian Zhu
- grid.413405.70000 0004 1808 0686Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.413405.70000 0004 1808 0686Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.79703.3a0000 0004 1764 3838School of Medicine, South China University of Technology, Guangzhou, 510080 Guangdong China
| | - Min Qin
- grid.413405.70000 0004 1808 0686Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.413405.70000 0004 1808 0686Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.79703.3a0000 0004 1764 3838School of Medicine, South China University of Technology, Guangzhou, 510080 Guangdong China
| | - Zixian Wang
- grid.413405.70000 0004 1808 0686Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.413405.70000 0004 1808 0686Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China
| | - Yonglin Wu
- grid.413405.70000 0004 1808 0686Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.413405.70000 0004 1808 0686Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China
| | - Xiaoping Chen
- grid.452223.00000 0004 1757 7615Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008 Hunan China
| | - Chen Liu
- grid.412615.50000 0004 1803 6239Department of Cardiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080 Guangdong China
| | - Qilin Ma
- grid.452223.00000 0004 1757 7615Department of Cardiology, Xiangya Hospital, Central South University, Changsha, 410008 Hunan China
| | - Yibin Liu
- grid.413405.70000 0004 1808 0686Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.413405.70000 0004 1808 0686Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.79703.3a0000 0004 1764 3838School of Medicine, South China University of Technology, Guangzhou, 510080 Guangdong China
| | - Weihua Lai
- grid.413405.70000 0004 1808 0686Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China
| | - Hui Chen
- grid.413405.70000 0004 1808 0686Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.79703.3a0000 0004 1764 3838School of Medicine, South China University of Technology, Guangzhou, 510080 Guangdong China
| | - Jingjing Cai
- grid.49470.3e0000 0001 2331 6153Institute of Model Animal, Wuhan University, Wuhan, 430072 Hubei China
| | - Yemao Liu
- grid.49470.3e0000 0001 2331 6153Institute of Model Animal, Wuhan University, Wuhan, 430072 Hubei China
| | - Fang Lei
- grid.49470.3e0000 0001 2331 6153Institute of Model Animal, Wuhan University, Wuhan, 430072 Hubei China
| | - Bin Zhang
- grid.413405.70000 0004 1808 0686Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.79703.3a0000 0004 1764 3838School of Medicine, South China University of Technology, Guangzhou, 510080 Guangdong China
| | - Shuyao Zhang
- grid.258164.c0000 0004 1790 3548Department of Pharmacy, Guangzhou Red Cross Hospital, Jinan University, Guangzhou, 510220 Guangdong China
| | - Guodong He
- grid.413405.70000 0004 1808 0686Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.79703.3a0000 0004 1764 3838School of Medicine, South China University of Technology, Guangzhou, 510080 Guangdong China
| | - Hanping Li
- grid.413405.70000 0004 1808 0686Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China
| | - Mingliang Zhang
- Wuhan Metware Biotechnology Co., Ltd., Wuhan, 430000 Hubei China
| | - Hui Zheng
- Wuhan Metware Biotechnology Co., Ltd., Wuhan, 430000 Hubei China
| | - Jiyan Chen
- grid.413405.70000 0004 1808 0686Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China
| | - Min Huang
- grid.12981.330000 0001 2360 039XInstitute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006 Guangdong China
| | - Shilong Zhong
- grid.413405.70000 0004 1808 0686Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.413405.70000 0004 1808 0686Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China ,grid.79703.3a0000 0004 1764 3838School of Medicine, South China University of Technology, Guangzhou, 510080 Guangdong China
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13
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Berchuck SI, Jammal AA, Page D, Somers TJ, Medeiros FA. A Framework for Automating Psychiatric Distress Screening in Ophthalmology Clinics Using an EHR-Derived AI Algorithm. Transl Vis Sci Technol 2022; 11:6. [PMID: 36180026 PMCID: PMC9547354 DOI: 10.1167/tvst.11.10.6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 09/14/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose In patients with ophthalmic disorders, psychosocial risk factors play an important role in morbidity and mortality. Proper and early psychiatric screening can result in prompt intervention and mitigate its impact. Because screening is resource intensive, we developed a framework for automating screening using an electronic health record (EHR)-derived artificial intelligence (AI) algorithm. Methods Subjects came from the Duke Ophthalmic Registry, a retrospective EHR database for the Duke Eye Center. Inclusion criteria included at least two encounters and a minimum of 1 year of follow-up. Presence of distress was defined at the encounter level using a computable phenotype. Risk factors included available EHR history. At each encounter, risk factors were used to discriminate psychiatric status. Model performance was evaluated using area under the receiver operating characteristic (ROC) curve and area under the precision-recall curve (PR AUC). Variable importance was presented using odds ratios (ORs). Results Our cohort included 358,135 encounters from 40,326 patients with an average of nine encounters per patient over 4 years. The ROC and PR AUC were 0.91 and 0.55, respectively. Of the top 25 predictors, the majority were related to existing distress, but some indicated stressful conditions, including chemotherapy (OR = 1.36), esophageal disorders (OR = 1.31), central pain syndrome (OR = 1.25), and headaches (OR = 1.24). Conclusions Psychiatric distress in ophthalmology patients can be monitored passively using an AI algorithm trained on existing EHR data. Translational Relevance When paired with an effective referral and treatment program, such algorithms may improve health outcomes in ophthalmology.
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Affiliation(s)
| | - Alessandro A. Jammal
- Duke Eye Center and Department of Ophthalmology, Duke University, Durham, NC, USA
| | - David Page
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Tamara J. Somers
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Felipe A. Medeiros
- Duke Eye Center and Department of Ophthalmology, Duke University, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
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14
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Innovative Application of Metabolomics on Bioactive Ingredients of Foods. Foods 2022; 11:foods11192974. [PMID: 36230049 PMCID: PMC9562173 DOI: 10.3390/foods11192974] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/12/2022] [Accepted: 09/20/2022] [Indexed: 11/17/2022] Open
Abstract
Metabolomics, as a new omics technology, has been widely accepted by researchers and has shown great potential in the field of nutrition and health in recent years. This review briefly introduces the process of metabolomics analysis, including sample preparation and extraction, derivatization, separation and detection, and data processing. This paper focuses on the application of metabolomics in food-derived bioactive ingredients. For example, metabolomics techniques are used to analyze metabolites in food to find bioactive substances or new metabolites in food materials. Moreover, bioactive substances have been tested in vitro and in vivo, as well as in humans, to investigate the changes of metabolites and the underlying metabolic pathways, among which metabolomics is used to find potential biomarkers and targets. Metabolomics provides a new approach for the prevention and regulation of chronic diseases and the study of the underlying mechanisms. It also provides strong support for the development of functional food or drugs. Although metabolomics has some limitations such as low sensitivity, poor repeatability, and limited detection range, it is developing rapidly in general, and also in the field of nutrition and health. At the end of this paper, we put forward our own insights on the development prospects of metabolomics in the application of bioactive ingredients in food.
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15
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Doğan HO, Şenol O, Karadağ A, Yıldız SN. Metabolomic profiling in ankylosing spondylitis using time-of-flight mass spectrometry. Clin Nutr ESPEN 2022; 50:124-132. [PMID: 35871913 DOI: 10.1016/j.clnesp.2022.06.011] [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: 10/28/2021] [Revised: 04/19/2022] [Accepted: 06/15/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND & AIMS Ankylosing spondylitis (AS) is an inflammatory disease associated with destructive changes in the skeleton and joints. The exact molecular mechanism of the disease has not been fully elucidated. This study aimed to determine metabolic differences between active AS patients and healthy controls to understand the molecular mechanism of AS. PATIENTS AND METHODS The study included 38 subjects, comprising 18 patients with active AS and 20 healthy controls. Metabolic profiling of the plasma was performed using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC Q-TOF/MS). Data acquisition, classification, and identification were achieved with the METLIN (https://metlin.scripps.edu/) database and XCMS (https://xcmsonline.scripps.edu). RESULTS Significant alterations were identified in the unsaturated fatty acids (FA), linoleic acid, alpha-linolenic acid, FA degradation, and FA biosynthesis pathways. Down -regulations were observed in phosphatidylcholine (PC) (16:0/0:0), beta-d-Fructose, stearic acid, trimipramine N-Oxide and muconic acid, and up-regulation were detected in PC (18:2/0:0), 3-Methylindole, palmitic acid (PA), alpha-Tocotrienol, and beta-d-glucopyranoside in active AS patients compared to the healthy control subjects. CONCLUSION Pathway analysis revealed that dysregulation in FA metabolism is associated with AS, and therefore, modulation of diet according to PA and PC may be potential therapeutic targets.
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Affiliation(s)
- Halef Okan Doğan
- Department of Biochemistry, School of Medicine, University of Sivas Cumhuriyet, Sivas, Turkey.
| | - Onur Şenol
- Department of Analytical Chemistry, Faculty of Pharmacy, Atatürk University, Erzurum, Turkey
| | - Ahmet Karadağ
- Department of Pyhsical Medicine and Rehabilitation, School of Medicine, University of Sivas Cumhuriyet, Sivas, Turkey
| | - Seyma Nur Yıldız
- İzmir International Biomedicine and Genome Institute, Dokuz Eylül University, İzmir, Turkey
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16
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Cai C, Liu Y, Li J, Wang L, Zhang K. Serum fingerprinting by slippery liquid-infused porous SERS for non-invasive lung cancer detection. Analyst 2022; 147:4426-4432. [DOI: 10.1039/d2an01325h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Direct and label-free analysis of clinical serum samples using slippery liquid-infused porous-enhanced Raman spectroscopy (SLIPSERS) enables the rapid non-invasive identification of lung cancer.
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Affiliation(s)
- Chenlei Cai
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
| | - Yujie Liu
- Shanghai Institute for Pediatric Research, Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China
| | - Jiayu Li
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
| | - Lei Wang
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
| | - Kun Zhang
- Shanghai Institute for Pediatric Research, Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China
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17
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Nambiar S, Clynick B, How BS, King A, Walters EH, Goh NS, Corte TJ, Trengove R, Tan D, Moodley Y. There is detectable variation in the lipidomic profile between stable and progressive patients with idiopathic pulmonary fibrosis (IPF). Respir Res 2021; 22:105. [PMID: 33836757 PMCID: PMC8033725 DOI: 10.1186/s12931-021-01682-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 03/11/2021] [Indexed: 01/10/2023] Open
Abstract
Background Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease characterized by fibrosis and progressive loss of lung function. The pathophysiological pathways involved in IPF are not well understood. Abnormal lipid metabolism has been described in various other chronic lung diseases including asthma and chronic obstructive pulmonary disease (COPD). However, its potential role in IPF pathogenesis remains unclear. Methods In this study, we used ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) to characterize lipid changes in plasma derived from IPF patients with stable and progressive disease. We further applied a data-independent acquisition (DIA) technique called SONAR, to improve the specificity of lipid identification. Results Statistical modelling showed variable discrimination between the stable and progressive subjects, revealing differences in the detection of triglycerides (TG) and phosphatidylcholines (PC) between progressors and stable IPF groups, which was further confirmed by mass spectrometry imaging (MSI) in IPF tissue. Conclusion This is the first study to characterise lipid metabolism between stable and progressive IPF, with results suggesting disparities in the circulating lipidome with disease progression.
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Affiliation(s)
- Shabarinath Nambiar
- Separation Science and Metabolomics Laboratory, Murdoch University, Murdoch, WA, Australia
| | - Britt Clynick
- School of Biomedical Science, University of Western Australia, Crawley, WA, Australia. .,Institute for Respiratory Health, Nedlands, WA, Australia.
| | - Bong S How
- Separation Science and Metabolomics Laboratory, Murdoch University, Murdoch, WA, Australia.,Metabolomics Australia, Murdoch University, Murdoch, WA, Australia
| | - Adam King
- Scientific Operations, Waters Corporation, Stamford Avenue, Wilmslow, SK9 4AX, UK
| | - E Haydn Walters
- Alfred Hospital, Melbourne, VIC, Australia.,University of Tasmania, Hobart, TAS, Australia.,University of Melbourne, Parkville, VIC, Australia.,Royal Hobart Hospital, Hobart, TAS, Australia
| | - Nicole S Goh
- Austin Hospital, Heidelberg, VIC, Australia.,Institute of Breathing and Sleep, Heidelberg, VIC, Australia
| | - Tamera J Corte
- University of Sydney, Camperdown, NSW, Australia.,Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | - Robert Trengove
- Separation Science and Metabolomics Laboratory, Murdoch University, Murdoch, WA, Australia.,Metabolomics Australia, Murdoch University, Murdoch, WA, Australia
| | - Dino Tan
- School of Biomedical Science, University of Western Australia, Crawley, WA, Australia.,Institute for Respiratory Health, Nedlands, WA, Australia
| | - Yuben Moodley
- School of Biomedical Science, University of Western Australia, Crawley, WA, Australia.,Institute for Respiratory Health, Nedlands, WA, Australia.,Fiona Stanley Hospital, Murdoch, WA, Australia
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18
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Clark C, Bettenhausen HM, Heuberger AL, Miller J, Yao L, Stone M. Effects of time and temperature during melanging on the volatile profile of dark chocolate. Sci Rep 2020; 10:14922. [PMID: 32913253 PMCID: PMC7483446 DOI: 10.1038/s41598-020-71822-0] [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: 01/21/2020] [Accepted: 08/13/2020] [Indexed: 12/20/2022] Open
Abstract
Chocolate made from small-batch production is known for distinct sensory properties that differentiate its products from large-scale production. Specifically, small-batch processing includes a melanging step, a chocolate refining (a process involving time and temperature to refine texture and flavor) process that occurs in a stone wet-grinder. Chocolatiers understand that melanging is essential to flavor and overall quality, however the influence of melanging on the aroma chemistry of the finished chocolate is anecdotal and largely uncharacterized. Here, we evaluated the effects of time and temperature of melanging on the volatile chemistry of the finished chocolate. Specifically, chocolate aroma was profiled using HS/SPME-GC-MS for three different time and temperature combinations. A total of 88 compounds were annotated by mass spectrometry and included a diverse set of chemical classes such as pyrazines, aldehydes, terpenes, alcohols, esters, and ketones. Analysis of variance (ANOVA), principal component analysis (PCA), and partial least squares analysis (PLS) revealed that the overall aroma profile was influenced by the type of melanging, and time had a greater effect than temperature. Example compounds affected by time include 2-methylpropanal, dimethyl sulfide, and benzaldehyde. Particle size was also measured for each sample. Majority particle size was found to be below 25 microns generally at all time points beyond 8 h. Analysis showed significant p-values for the temperature variable for several compounds, but significant p-values for the time variable were apparent for a greater number of compounds. For compounds which showed dependency on both time and temperature, the p-value for the time variable was much smaller in most cases. Both PCA and OPLS analyses suggested the same trends. These data support that time is a critical factor in determining the aroma chemistry of chocolate and affects a diverse set of known flavor active compounds.
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Affiliation(s)
- Caitlin Clark
- Department of Food Science and Human Nutrition, Colorado State University, Fort Collins,, CO, USA.
- Nuance Chocolate, Fort Collins, CO, USA.
| | - Harmonie M Bettenhausen
- Department of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO, USA
| | - Adam L Heuberger
- Department of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO, USA
| | - Jeffrey Miller
- Department of Food Science and Human Nutrition, Colorado State University, Fort Collins,, CO, USA
- Nuance Chocolate, Fort Collins, CO, USA
| | - Linxing Yao
- Proteomics and Metabolomics Facility, Colorado State University, Fort Collins, CO, USA
| | - Martha Stone
- Department of Food Science and Human Nutrition, Colorado State University, Fort Collins,, CO, USA
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19
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Franco J, Rajwa B, Ferreira CR, Sundberg JP, HogenEsch H. Lipidomic Profiling of the Epidermis in a Mouse Model of Dermatitis Reveals Sexual Dimorphism and Changes in Lipid Composition before the Onset of Clinical Disease. Metabolites 2020; 10:metabo10070299. [PMID: 32708296 PMCID: PMC7408197 DOI: 10.3390/metabo10070299] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 07/17/2020] [Accepted: 07/18/2020] [Indexed: 02/07/2023] Open
Abstract
Atopic dermatitis (AD) is a multifactorial disease associated with alterations in lipid composition and organization in the epidermis. Multiple variants of AD exist with different outcomes in response to therapies. The evaluation of disease progression and response to treatment are observational assessments with poor inter-observer agreement highlighting the need for molecular markers. SHARPIN-deficient mice (Sharpincpdm) spontaneously develop chronic proliferative dermatitis with features similar to AD in humans. To study the changes in the epidermal lipid-content during disease progression, we tested 72 epidermis samples from three groups (5-, 7-, and 10-weeks old) of cpdm mice and their WT littermates. An agnostic mass-spectrometry strategy for biomarker discovery termed multiple-reaction monitoring (MRM)-profiling was used to detect and monitor 1,030 lipid ions present in the epidermis samples. In order to select the most relevant ions, we utilized a two-tiered filter/wrapper feature-selection strategy. Lipid categories were compressed, and an elastic-net classifier was used to rank and identify the most predictive lipid categories for sex, phenotype, and disease stages of cpdm mice. The model accurately classified the samples based on phospholipids, cholesteryl esters, acylcarnitines, and sphingolipids, demonstrating that disease progression cannot be defined by one single lipid or lipid category.
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Affiliation(s)
- Jackeline Franco
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA;
| | - Bartek Rajwa
- Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA
- Correspondence: (B.R.); (H.H.)
| | - Christina R. Ferreira
- Metabolite Profiling Facility, Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA;
| | | | - Harm HogenEsch
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA;
- Purdue Institute of Inflammation, Immunology and Infectious Diseases, Purdue University, West Lafayette, IN 47907, USA
- Correspondence: (B.R.); (H.H.)
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20
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Label-free plasma proteomics identifies haptoglobin-related protein as candidate marker of idiopathic pulmonary fibrosis and dysregulation of complement and oxidative pathways. Sci Rep 2020; 10:7787. [PMID: 32385381 PMCID: PMC7211010 DOI: 10.1038/s41598-020-64759-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 04/19/2020] [Indexed: 02/06/2023] Open
Abstract
Idiopathic pulmonary fibrosis (IPF) is a lung parenchymal disease of unknown cause usually occurring in older adults. It is a chronic and progressive condition with poor prognosis and diagnosis is largely clinical. Currently, there exist few biomarkers that can predict patient outcome or response to therapies. Together with lack of markers, the need for novel markers for the detection and monitoring of IPF, is paramount. We have performed label-free plasma proteomics of thirty six individuals, 17 of which had confirmed IPF. Proteomics data was analyzed by volcano plot, hierarchical clustering, Partial-least square discriminant analysis (PLS-DA) and Ingenuity pathway analysis. Univariate and multivariate statistical analysis overlap identified haptoglobin-related protein as a possible marker of IPF when compared to control samples (Area under the curve 0.851, ROC-analysis). LXR/RXR activation and complement activation pathways were enriched in t-test significant proteins and oxidative regulators, complement proteins and protease inhibitors were enriched in PLS-DA significant proteins. Our pilot study points towards aberrations in complement activation and oxidative damage in IPF patients and provides haptoglobin-related protein as a new candidate biomarker of IPF.
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Vergara-Diaz O, Vatter T, Kefauver SC, Obata T, Fernie AR, Araus JL. Assessing durum wheat ear and leaf metabolomes in the field through hyperspectral data. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 102:615-630. [PMID: 31808224 DOI: 10.1111/tpj.14636] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 11/13/2019] [Accepted: 11/21/2019] [Indexed: 05/24/2023]
Abstract
Hyperspectral techniques are currently used to retrieve information concerning plant biophysical traits, predominantly targeting pigments, water, and nitrogen-protein contents, structural elements, and the leaf area index. Even so, hyperspectral data could be more extensively exploited to overcome the breeding challenges being faced under global climate change by advancing high-throughput field phenotyping. In this study, we explore the potential of field spectroscopy to predict the metabolite profiles in flag leaves and ear bracts in durum wheat. The full-range reflectance spectra (visible (VIS)-near-infrared (NIR)-short wave infrared (SWIR)) of flag leaves, ears and canopies were recorded in a collection of contrasting genotypes grown in four environments under different water regimes. GC-MS metabolite profiles were analyzed in the flag leaves, ear bracts, glumes, and lemmas. The results from regression models exceeded 50% of the explained variation (adj-R2 in the validation sets) for at least 15 metabolites in each plant organ, whereas their errors were considerably low. The best regressions were obtained for malate (82%), glycerate and serine (63%) in leaves; myo-inositol (81%) in lemmas; glycolate (80%) in glumes; sucrose in leaves and glumes (68%); γ-aminobutyric acid (GABA) in leaves and glumes (61% and 71%, respectively); proline and glucose in lemmas (74% and 71%, respectively) and glumes (72% and 69%, respectively). The selection of wavebands in the models and the performance of the models based on canopy and VIS organ spectra and yield prediction are discussed. We feel that this technique will likely to be of interest due to its broad applicability in ecophysiology research, plant breeding programmes, and the agri-food industry.
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Affiliation(s)
- Omar Vergara-Diaz
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, Diagonal 643, 08028, Barcelona, Spain
| | - Thomas Vatter
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, Diagonal 643, 08028, Barcelona, Spain
| | - Shawn Carlisle Kefauver
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, Diagonal 643, 08028, Barcelona, Spain
| | - Toshihiro Obata
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam, Germany
| | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam, Germany
| | - José Luis Araus
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, Diagonal 643, 08028, Barcelona, Spain
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22
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Vergara-Diaz O, Vatter T, Vicente R, Obata T, Nieto-Taladriz MT, Aparicio N, Carlisle Kefauver S, Fernie A, Araus JL. Metabolome Profiling Supports the Key Role of the Spike in Wheat Yield Performance. Cells 2020; 9:E1025. [PMID: 32326207 PMCID: PMC7226616 DOI: 10.3390/cells9041025] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/07/2020] [Accepted: 04/15/2020] [Indexed: 11/30/2022] Open
Abstract
Although the relevance of spike bracts in stress acclimation and contribution to wheat yield was recently revealed, the metabolome of this organ and its response to water stress is still unknown. The metabolite profiles of flag leaves, glumes and lemmas were characterized under contrasting field water regimes in five durum wheat cultivars. Water conditions during growth were characterized through spectral vegetation indices, canopy temperature and isotope composition. Spike bracts exhibited better coordination of carbon and nitrogen metabolisms than the flag leaves in terms of photorespiration, nitrogen assimilation and respiration paths. This coordination facilitated an accumulation of organic and amino acids in spike bracts, especially under water stress. The metabolomic response to water stress also involved an accumulation of antioxidant and drought tolerance related sugars, particularly in the spikes. Furthermore, certain cell wall, respiratory and protective metabolites were associated with genotypic outperformance and yield stability. In addition, grain yield was strongly predicted by leaf and spike bracts metabolomes independently. This study supports the role of the spike as a key organ during wheat grain filling, particularly under stress conditions and provides relevant information to explore new ways to improve wheat productivity including potential biomarkers for yield prediction.
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Affiliation(s)
- Omar Vergara-Diaz
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, Diagonal 643, 08028 Barcelona, Spain; (O.V.-D.); (T.V.); (R.V.); (S.C.K.)
- AGROTECNIO (Center of Research in Agrotechnology), 25198 Lleida, Spain
| | - Thomas Vatter
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, Diagonal 643, 08028 Barcelona, Spain; (O.V.-D.); (T.V.); (R.V.); (S.C.K.)
- AGROTECNIO (Center of Research in Agrotechnology), 25198 Lleida, Spain
| | - Rubén Vicente
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, Diagonal 643, 08028 Barcelona, Spain; (O.V.-D.); (T.V.); (R.V.); (S.C.K.)
- AGROTECNIO (Center of Research in Agrotechnology), 25198 Lleida, Spain
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany; (T.O.); (A.F.)
| | - Toshihiro Obata
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany; (T.O.); (A.F.)
| | - Maria Teresa Nieto-Taladriz
- National Institute for Agricultural and Food Research and Technology (INIA), Ctra de la Coruña 7.5, 28040 Madrid, Spain;
| | - Nieves Aparicio
- Technological and Agrarian Institute of Castilla y León (ITACyL), Agricultural Research. Ctra Burgos km 119, 47041 Valladolid, Spain;
| | - Shawn Carlisle Kefauver
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, Diagonal 643, 08028 Barcelona, Spain; (O.V.-D.); (T.V.); (R.V.); (S.C.K.)
- AGROTECNIO (Center of Research in Agrotechnology), 25198 Lleida, Spain
| | - Alisdair Fernie
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany; (T.O.); (A.F.)
| | - José Luis Araus
- Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, Diagonal 643, 08028 Barcelona, Spain; (O.V.-D.); (T.V.); (R.V.); (S.C.K.)
- AGROTECNIO (Center of Research in Agrotechnology), 25198 Lleida, Spain
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23
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Schlueter RJ, Al-Akwaa FM, Benny PA, Gurary A, Xie G, Jia W, Chun SJ, Chern I, Garmire LX. Prepregnant Obesity of Mothers in a Multiethnic Cohort Is Associated with Cord Blood Metabolomic Changes in Offspring. J Proteome Res 2020; 19:1361-1374. [PMID: 31975597 DOI: 10.1021/acs.jproteome.9b00319] [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] [Indexed: 12/30/2022]
Abstract
Maternal obesity has become a growing global health concern that may predispose the offspring to medical conditions later in life. However, the metabolic link between maternal prepregnant obesity and healthy offspring has not yet been fully elucidated. In this study, we conducted a case-control study using a coupled untargeted and targeted metabolomic approach from the newborn cord blood metabolomes associated with a matched maternal prepregnant obesity cohort of 28 cases and 29 controls. The subjects were recruited from multiethnic populations in Hawaii, including rarely reported Native Hawaiian and other Pacific Islanders (NHPI). We found that maternal obesity was the most important factor contributing to differences in cord blood metabolomics. Using an elastic net regularization-based logistic regression model, we identified 29 metabolites as potential early-life biomarkers manifesting intrauterine effect of maternal obesity, with accuracy as high as 0.947 after adjusting for clinical confounding (maternal and paternal age, ethnicity, parity, and gravidity). We validated the model results in a subsequent set of samples (N = 30) with an accuracy of 0.822. Among the metabolites, six metabolites (galactonic acid, butenylcarnitine, 2-hydroxy-3-methylbutyric acid, phosphatidylcholine diacyl C40:3, 1,5-anhydrosorbitol, and phosphatidylcholine acyl-alkyl 40:3) were individually and significantly different between the maternal obese and normal-weight groups. Interestingly, hydroxy-3-methylbutyric acid showed significantly higher levels in cord blood from the NHPI group compared to that from Asian and Caucasian groups. In summary, significant associations were observed between maternal prepregnant obesity and offspring metabolomic alternation at birth, revealing the intergenerational impact of maternal obesity.
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Affiliation(s)
- Ryan J Schlueter
- Department of Obstetrics and Gynecology, University of Hawaii, 1319 Punahou St Ste 824, Honolulu, Hawaii 96826, United States
| | - Fadhl M Al-Akwaa
- Department of Computational Medicine and Bioinformatics, North Campus Research Complex, University of Michigan, 1600 Huron Parkway, Ann Arbor, Michigan 48105, United States
| | - Paula A Benny
- Department of Epidemiology, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, Hawaii 96813, United States
| | - Alexandra Gurary
- John A. Burns School of Medicine, Department of Tropical Medicine, Medical Microbiology and Pharmacology, University of Hawaii, 651 Ilalo Street, Bioscience Building 320, Honolulu, Hawaii 96813, United States
| | - Guoxiang Xie
- Metabolomics Shared Resource, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, Hawaii 96813, United States
| | - Wei Jia
- Metabolomics Shared Resource, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, Hawaii 96813, United States
| | - Shaw J Chun
- Department of Epidemiology, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, Hawaii 96813, United States
| | - Ingrid Chern
- Department of Obstetrics and Gynecology, University of Hawaii, 1319 Punahou St Ste 824, Honolulu, Hawaii 96826, United States
| | - Lana X Garmire
- Department of Computational Medicine and Bioinformatics, North Campus Research Complex, University of Michigan, 1600 Huron Parkway, Ann Arbor, Michigan 48105, United States
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24
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Unravelling the Metabolic Reconfiguration of the Post-Challenge Primed State in Sorghum bicolor Responding to Colletotrichum sublineolum Infection. Metabolites 2019; 9:metabo9100194. [PMID: 31547091 PMCID: PMC6835684 DOI: 10.3390/metabo9100194] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 09/13/2019] [Accepted: 09/16/2019] [Indexed: 12/15/2022] Open
Abstract
Priming is a natural phenomenon that pre-conditions plants for enhanced defence against a wide range of pathogens. It represents a complementary strategy, or sustainable alternative that can provide protection against disease. However, a comprehensive functional and mechanistic understanding of the various layers of priming events is still limited. A non-targeted metabolomics approach was used to investigate metabolic changes in plant growth-promoting rhizobacteria (PGPR)-primed Sorghum bicolor seedlings infected with the anthracnose-causing fungal pathogen, Colletotrichum sublineolum, with a focus on the post-challenge primed state phase. At the 4-leaf growth stage, the plants were treated with a strain of Paenibacillus alvei at 108 cfu mL−1. Following a 24 h PGPR application, the plants were inoculated with a C. sublineolum spore suspension (106 spores mL−1), and the infection monitored over time: 1, 3, 5, 7 and 9 days post-inoculation. Non-infected plants served as negative controls. Intracellular metabolites from both inoculated and non-inoculated plants were extracted with 80% methanol-water. The extracts were chromatographically and spectrometrically analysed on an ultra-high performance liquid chromatography (UHPLC) system coupled to high-definition mass spectrometry. The acquired multidimensional data were processed to create data matrices for chemometric modelling. The computed models indicated time-related metabolic perturbations that reflect primed responses to the fungal infection. Evaluation of orthogonal projection to latent structure-discriminant analysis (OPLS-DA) loading shared and unique structures (SUS)-plots uncovered the differential stronger defence responses against the fungal infection observed in primed plants. These involved enhanced levels of amino acids (tyrosine, tryptophan), phytohormones (jasmonic acid and salicylic acid conjugates, and zeatin), and defence-related components of the lipidome. Furthermore, other defence responses in both naïve and primed plants were characterised by a complex mobilisation of phenolic compounds and de novo biosynthesis of the flavones, apigenin and luteolin and the 3-deoxyanthocyanidin phytoalexins, apigeninidin and luteolinidin, as well as some related conjugates.
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25
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Laíns I, Gantner M, Murinello S, Lasky-Su JA, Miller JW, Friedlander M, Husain D. Metabolomics in the study of retinal health and disease. Prog Retin Eye Res 2018; 69:57-79. [PMID: 30423446 DOI: 10.1016/j.preteyeres.2018.11.002] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 10/06/2018] [Accepted: 11/07/2018] [Indexed: 02/06/2023]
Abstract
Metabolomics is the qualitative and quantitative assessment of the metabolites (small molecules < 1.5 kDa) in body fluids. The metabolites are the downstream of the genetic transcription and translation processes and also downstream of the interactions with environmental exposures; thus, they are thought to closely relate to the phenotype, especially for multifactorial diseases. In the last decade, metabolomics has been increasingly used to identify biomarkers in disease, and it is currently recognized as a very powerful tool with great potential for clinical translation. The metabolome and the associated pathways also help improve our understanding of the pathophysiology and mechanisms of disease. While there has been increasing interest and research in metabolomics of the eye, the application of metabolomics to retinal diseases has been limited, even though these are leading causes of blindness. In this manuscript, we perform a comprehensive summary of the tools and knowledge required to perform a metabolomics study, and we highlight essential statistical methods for rigorous study design and data analysis. We review available protocols, summarize the best approaches, and address the current unmet need for information on collection and processing of tissues and biofluids that can be used for metabolomics of retinal diseases. Additionally, we critically analyze recent work in this field, both in animal models and in human clinical disease, including diabetic retinopathy and age-related macular degeneration. Finally, we identify opportunities for future research applying metabolomics to improve our current assessment and understanding of mechanisms of vitreoretinal diseases, and to hence improve patient assessment and care.
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Affiliation(s)
- Inês Laíns
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, United States; Faculty of Medicine, University of Coimbra, 3000 Coimbra, Portugal.
| | - Mari Gantner
- Lowy Medical Research Institute, La Jolla, CA, 92037, United States; Scripps Research Institute, La Jolla, CA, 92037, United States.
| | - Salome Murinello
- Lowy Medical Research Institute, La Jolla, CA, 92037, United States; Scripps Research Institute, La Jolla, CA, 92037, United States.
| | - Jessica A Lasky-Su
- Systems Genetics and Genomics Unit, Channing Division of Network Medicine Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02115, United States.
| | - Joan W Miller
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, United States.
| | - Martin Friedlander
- Lowy Medical Research Institute, La Jolla, CA, 92037, United States; Scripps Research Institute, La Jolla, CA, 92037, United States.
| | - Deeba Husain
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, United States.
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26
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Kirpich A, Ainsworth EA, Wedow JM, Newman JRB, Michailidis G, McIntyre LM. Variable selection in omics data: A practical evaluation of small sample sizes. PLoS One 2018; 13:e0197910. [PMID: 29927942 PMCID: PMC6013185 DOI: 10.1371/journal.pone.0197910] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2017] [Accepted: 05/10/2018] [Indexed: 01/04/2023] Open
Abstract
In omics experiments, variable selection involves a large number of metabolites/ genes and a small number of samples (the n < p problem). The ultimate goal is often the identification of one, or a few features that are different among conditions- a biomarker. Complicating biomarker identification, the p variables often contain a correlation structure due to the biology of the experiment making identifying causal compounds from correlated compounds difficult. Additionally, there may be elements in the experimental design (blocks, batches) that introduce structure in the data. While this problem has been discussed in the literature and various strategies proposed, the over fitting problems concomitant with such approaches are rarely acknowledged. Instead of viewing a single omics experiment as a definitive test for a biomarker, an unrealistic analytical goal, we propose to view such studies as screening studies where the goal of the study is to reduce the number of features present in the second round of testing, and to limit the Type II error. Using this perspective, the performance of LASSO, ridge regression and Elastic Net was compared with the performance of an ANOVA via a simulation study and two real data comparisons. Interestingly, a dramatic increase in the number of features had no effect on Type I error for the ANOVA approach. ANOVA, even without multiple test correction, has a low false positive rates in the scenarios tested. The Elastic Net has an inflated Type I error (from 10 to 50%) for small numbers of features which increases with sample size. The Type II error rate for the ANOVA is comparable or lower than that for the Elastic Net leading us to conclude that an ANOVA is an effective analytical tool for the initial screening of features in omics experiments.
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Affiliation(s)
- Alexander Kirpich
- Department of Biology, University of Florida, Gainesville, FL, United States of America
- Informatics Institute, University of Florida, Gainesville, FL, United States of America
| | - Elizabeth A. Ainsworth
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
- USDA ARS Global Change and Photosynthesis Research Unit, Urbana, IL, United States of America
| | - Jessica M. Wedow
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
| | - Jeremy R. B. Newman
- Department of Biology, University of Florida, Gainesville, FL, United States of America
| | - George Michailidis
- Informatics Institute, University of Florida, Gainesville, FL, United States of America
- Department of Statistics, University of Florida, Gainesville, FL, United States of America
| | - Lauren M. McIntyre
- Department of Biology, University of Florida, Gainesville, FL, United States of America
- Informatics Institute, University of Florida, Gainesville, FL, United States of America
- Genetics Institute, University of Florida, Gainesville, FL, United States of America
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Problematic internet use as an age-related multifaceted problem: Evidence from a two-site survey. Addict Behav 2018; 81:157-166. [PMID: 29459201 PMCID: PMC5849299 DOI: 10.1016/j.addbeh.2018.02.017] [Citation(s) in RCA: 99] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Revised: 02/09/2018] [Accepted: 02/10/2018] [Indexed: 12/20/2022]
Abstract
BACKGROUND AND AIMS Problematic internet use (PIU; otherwise known as Internet Addiction) is a growing problem in modern societies. There is scarce knowledge of the demographic variables and specific internet activities associated with PIU and a limited understanding of how PIU should be conceptualized. Our aim was to identify specific internet activities associated with PIU and explore the moderating role of age and gender in those associations. METHODS We recruited 1749 participants aged 18 and above via media advertisements in an Internet-based survey at two sites, one in the US, and one in South Africa; we utilized Lasso regression for the analysis. RESULTS Specific internet activities were associated with higher problematic internet use scores, including general surfing (lasso β: 2.1), internet gaming (β: 0.6), online shopping (β: 1.4), use of online auction websites (β: 0.027), social networking (β: 0.46) and use of online pornography (β: 1.0). Age moderated the relationship between PIU and role-playing-games (β: 0.33), online gambling (β: 0.15), use of auction websites (β: 0.35) and streaming media (β: 0.35), with older age associated with higher levels of PIU. There was inconclusive evidence for gender and gender × internet activities being associated with problematic internet use scores. Attention-deficit hyperactivity disorder (ADHD) and social anxiety disorder were associated with high PIU scores in young participants (age ≤ 25, β: 0.35 and 0.65 respectively), whereas generalized anxiety disorder (GAD) and obsessive-compulsive disorder (OCD) were associated with high PIU scores in the older participants (age > 55, β: 6.4 and 4.3 respectively). CONCLUSIONS Many types of online behavior (e.g. shopping, pornography, general surfing) bear a stronger relationship with maladaptive use of the internet than gaming supporting the diagnostic classification of problematic internet use as a multifaceted disorder. Furthermore, internet activities and psychiatric diagnoses associated with problematic internet use vary with age, with public health implications.
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28
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Gonzales GB, De Saeger S. Elastic net regularized regression for time-series analysis of plasma metabolome stability under sub-optimal freezing condition. Sci Rep 2018; 8:3659. [PMID: 29483546 PMCID: PMC5826937 DOI: 10.1038/s41598-018-21851-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 02/06/2018] [Indexed: 12/11/2022] Open
Abstract
In this paper, the stability of the plasma metabolome at −20 °C for up to 30 days was evaluated using liquid chromatography-high resolution mass spectrometric metabolomics analysis. To follow the time-series deterioration of the plasma metabolome, the use of an elastic net regularized regression model for the prediction of storage time at −20 °C based on the plasma metabolomic profile, and the selection and ranking of metabolites with high temporal changes was demonstrated using the glmnet package in R. Out of 1229 (positive mode) and 1483 (negative mode) metabolite features, the elastic net model extracted 32 metabolites of interest in both positive and negative modes. L-gamma-glutamyl-L-(iso)leucine (tentative identification) was found to have the highest time-dependent change and significantly increased proportionally to the storage time of plasma at −20 °C (R2 = 0.6378 [positive mode], R2 = 0.7893 [negative mode], p-value < 0.00001). Based on the temporal profiles of the extracted metabolites by the model, results show only minimal deterioration of the plasma metabolome at −20 °C up to 1 month. However, majority of the changes appeared at around 12–15 days of storage. This allows scientists to better plan logistics and storage strategies for samples obtained from low-resource settings, where −80 °C storage is not guaranteed.
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Affiliation(s)
- Gerard Bryan Gonzales
- Gastroenterology and Hepatology, Department of Internal Medicine, Faculty of Medicine and Health Sciences, Ghent University, C. Heymanslaan 10, 9000, Ghent, Belgium. .,Laboratory of Food Analysis, Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium.
| | - Sarah De Saeger
- Laboratory of Food Analysis, Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium
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29
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Cuperlovic-Culf M. Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling. Metabolites 2018; 8:E4. [PMID: 29324649 PMCID: PMC5875994 DOI: 10.3390/metabo8010004] [Citation(s) in RCA: 80] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Revised: 01/08/2018] [Accepted: 01/09/2018] [Indexed: 01/15/2023] Open
Abstract
Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies.
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Affiliation(s)
- Miroslava Cuperlovic-Culf
- Digital Technologies Research Center, National Research Council of Canada, 1200 Montreal Road, Ottawa, ON K1A 0R6, Canada.
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30
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Wiczling P, Daghir-Wojtkowiak E, Yumba Mpanga A, Szczesny D, Kaliszan R, Markuszewski MJ. How to model temporal changes in nontargeted metabolomics study? A Bayesian multilevel perspective. J Sep Sci 2017; 40:4667-4676. [DOI: 10.1002/jssc.201700918] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Revised: 09/25/2017] [Accepted: 10/06/2017] [Indexed: 12/21/2022]
Affiliation(s)
- Paweł Wiczling
- Department of Biopharmaceutics and Pharmacodynamics; Medical University of Gdańsk; Gdańsk Poland
| | - Emilia Daghir-Wojtkowiak
- Department of Biopharmaceutics and Pharmacodynamics; Medical University of Gdańsk; Gdańsk Poland
| | - Arlette Yumba Mpanga
- Department of Biopharmaceutics and Pharmacodynamics; Medical University of Gdańsk; Gdańsk Poland
| | - Damian Szczesny
- Department of Biopharmaceutics and Pharmacodynamics; Medical University of Gdańsk; Gdańsk Poland
| | - Roman Kaliszan
- Department of Biopharmaceutics and Pharmacodynamics; Medical University of Gdańsk; Gdańsk Poland
| | - Michał Jan Markuszewski
- Department of Biopharmaceutics and Pharmacodynamics; Medical University of Gdańsk; Gdańsk Poland
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31
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Dudzik D, Barbas-Bernardos C, García A, Barbas C. Quality assurance procedures for mass spectrometry untargeted metabolomics. a review. J Pharm Biomed Anal 2017; 147:149-173. [PMID: 28823764 DOI: 10.1016/j.jpba.2017.07.044] [Citation(s) in RCA: 206] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Revised: 07/28/2017] [Accepted: 07/29/2017] [Indexed: 12/16/2022]
Abstract
Untargeted metabolomics, as a global approach, has already proven its great potential and capabilities for the investigation of health and disease, as well as the wide applicability for other research areas. Although great progress has been made on the feasibility of metabolomics experiments, there are still some challenges that should be faced and that includes all sources of fluctuations and bias affecting every step involved in multiplatform untargeted metabolomics studies. The identification and reduction of the main sources of unwanted variation regarding the pre-analytical, analytical and post-analytical phase of metabolomics experiments is essential to ensure high data quality. Nowadays, there is still a lack of information regarding harmonized guidelines for quality assurance as those available for targeted analysis. In this review, sources of variations to be considered and minimized along with methodologies and strategies for monitoring and improvement the quality of the results are discussed. The given information is based on evidences from different groups among our own experiences and recommendations for each stage of the metabolomics workflow. The comprehensive overview with tools presented here might serve other researchers interested in monitoring, controlling and improving the reliability of their findings by implementation of good experimental quality practices in the untargeted metabolomics study.
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Affiliation(s)
- Danuta Dudzik
- Center for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, San Pablo CEU University, Boadilla del Monte, ES-28668, Madrid, Spain.
| | - Cecilia Barbas-Bernardos
- Center for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, San Pablo CEU University, Boadilla del Monte, ES-28668, Madrid, Spain.
| | - Antonia García
- Center for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, San Pablo CEU University, Boadilla del Monte, ES-28668, Madrid, Spain.
| | - Coral Barbas
- Center for Metabolomics and Bioanalysis (CEMBIO), Faculty of Pharmacy, San Pablo CEU University, Boadilla del Monte, ES-28668, Madrid, Spain.
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