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Keywords = gout metabolomics

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13 pages, 293 KiB  
Review
Year in Review: Advances in Research in Gout Pathophysiology in 2024
by Rocio Paz Gonzalez and Monica Guma
Gout Urate Cryst. Depos. Dis. 2025, 3(3), 15; https://doi.org/10.3390/gucdd3030015 - 18 Aug 2025
Viewed by 251
Abstract
This review provides an overview of the most significant developments in gout pathophysiology research published in 2024. Thirteen studies were selected based on originality, scientific rigor, and potential clinical impact and grouped into four major categories: inflammation and pain mechanisms (LRRC8 anion channels, [...] Read more.
This review provides an overview of the most significant developments in gout pathophysiology research published in 2024. Thirteen studies were selected based on originality, scientific rigor, and potential clinical impact and grouped into four major categories: inflammation and pain mechanisms (LRRC8 anion channels, CXCL5-CXCR2 axis, CD38 and NAD+ metabolism, PLK1 and NLRP3 inflammasome localization, and IFN1 suppression), biomarkers and proteomics (scRNA-seq reveals monocyte and T-cell flare signatures, and Olink serum profiling reveals a proinflammatory signature in hyperuricemia and also identifies TNFSF14 as a novel flare biomarker, while a multi-omics integrative study implicates TRIM46 as a key causal gene), gut virome, and novel therapies (vagus nerve stimulation, biomimetic nanosystem, and restoration of Urate Oxidase (Uox) function). The studies selected focused primarily on work on subjects other than on hyperuricemia. The findings collectively expand our understanding of gout’s complex pathophysiology and highlight potential strategies for diagnosis, management, and innovative treatments. Full article
16 pages, 5025 KiB  
Article
Transcriptomic and Metabolomic Analysis Reveals the Impact of Autophagy Regulation on Purine Content in Mutton
by Xu Han, Yang Chen, Dandan Tan, Cuiyu Lai, Xuewen Han, Jinlin Chen, Yu Fu, Xuesong Shan and Huaizhi Jiang
Foods 2025, 14(5), 718; https://doi.org/10.3390/foods14050718 - 20 Feb 2025
Cited by 1 | Viewed by 872
Abstract
Background: Excessive purine intake increases the risk of hyperuricemia and gout. This study investigates the relationship between purine content in mutton and meat quality traits and explores the regulatory mechanism of purine metabolism through transcriptomic and metabolomic analyses. Methods: Thirty-six-month-old hybrid sheep (Australian [...] Read more.
Background: Excessive purine intake increases the risk of hyperuricemia and gout. This study investigates the relationship between purine content in mutton and meat quality traits and explores the regulatory mechanism of purine metabolism through transcriptomic and metabolomic analyses. Methods: Thirty-six-month-old hybrid sheep (Australian White × Small-tail Han) were selected. Purine content and meat quality traits, including inosine monophosphate (IMP), intramuscular fat (IMF), shear force, pH, cooking loss, and meat color, were measured. Transcriptomic sequencing and metabolomic analysis were performed on muscle samples with high (3895.70 ± 107.03 mg/kg) and low (2751.72 ± 175.29 mg/kg) purine contents (n = 6 per group). Differentially expressed genes were validated by quantitative PCR and Western blot. In vivo autophagy regulation experiments were performed on mice using rapamycin (activator) and chloroquine (inhibitor). Results: No significant correlation was found between purine content and meat quality traits, suggesting that reducing purine content does not negatively affect mutton quality. An autophagy-related gene, LAPTM5 (lysosomal-associated protein transmembrane 5), was identified as a key gene negatively regulating purine content. In vivo autophagy regulation experiments demonstrated that autophagy affects purine metabolism by modulating key enzymes such as xanthine dehydrogenase (XDH) and hypoxanthine-guanine phosphoribosyltransferase 1 (HPRT). Conclusions: This study reveals the role of autophagy in regulating purine metabolism through the key enzymes XDH and HPRT, providing new insights for improving mutton quality in the future. Full article
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16 pages, 954 KiB  
Review
Gout Basic Research: 2023 in Review
by Maria Muntiu, Leo A. B. Joosten and Tania O. Crişan
Gout Urate Cryst. Depos. Dis. 2024, 2(3), 220-235; https://doi.org/10.3390/gucdd2030017 - 31 Jul 2024
Cited by 3 | Viewed by 4559
Abstract
Gout is a prevalent form of inflammatory arthritis caused by the crystallization of uric acid in the joints and soft tissues, leading to acute, painful attacks. Activation of the NLRP3 inflammasome in mononuclear cells, along with inflammasome-independent pathways, is responsible for the inflammatory [...] Read more.
Gout is a prevalent form of inflammatory arthritis caused by the crystallization of uric acid in the joints and soft tissues, leading to acute, painful attacks. Activation of the NLRP3 inflammasome in mononuclear cells, along with inflammasome-independent pathways, is responsible for the inflammatory phenotype in gout. Research into the different aspects of gout pathophysiology and potential treatment options is ongoing. This review highlights some of the basic research published in the 12 months following the 2022 Gout, Hyperuricemia, and Crystal-Associated Disease Network (G-CAN) conference and focuses on mechanisms of inflammation, encompassing pro- and anti-inflammatory pathways, as well as the exploration of various biological systems, such as single-cell transcriptomics, proteomics, metabolomics, and microbiome analyses. Full article
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16 pages, 3084 KiB  
Article
Plasma and Urinary Metabolomic Analysis of Gout and Asymptomatic Hyperuricemia and Profiling of Potential Biomarkers: A Pilot Study
by Yuki Ohashi, Hiroshi Ooyama, Hideki Makinoshima, Tappei Takada, Hirotaka Matsuo and Kimiyoshi Ichida
Biomedicines 2024, 12(2), 300; https://doi.org/10.3390/biomedicines12020300 - 27 Jan 2024
Cited by 5 | Viewed by 3435
Abstract
Gout results from monosodium urate deposition caused by hyperuricemia, but most individuals with hyperuricemia remain asymptomatic. The pathogenesis of gout remains uncertain. To identify potential biomarkers distinguishing gout from asymptomatic hyperuricemia, we conducted a genetic analysis of urate transporters and metabolomic analysis as [...] Read more.
Gout results from monosodium urate deposition caused by hyperuricemia, but most individuals with hyperuricemia remain asymptomatic. The pathogenesis of gout remains uncertain. To identify potential biomarkers distinguishing gout from asymptomatic hyperuricemia, we conducted a genetic analysis of urate transporters and metabolomic analysis as a proof-of-concept study, including 33 patients with gout and 9 individuals with asymptomatic hyperuricemia. The variant allele frequencies of rs72552713, rs2231142, and rs3733591, which are related to serum urate levels (SUA) and gout, did not differ between the gout and asymptomatic hyperuricemia groups. In metabolomic analysis, the levels of citrate cycle intermediates, especially 2-ketoglutarate, were higher in patients with gout than in those with asymptomatic hyperuricemia (fold difference = 1.415, p = 0.039). The impact on the TCA cycle was further emphasized in high-risk gout (SUA ≥ 9.0 mg/dL). Of note, urinary nicotinate was the most prominent biomarker differentiating high-risk gout from asymptomatic hyperuricemia (fold difference = 6.515, p = 0.020). Although urate transporters play critical roles in SUA elevation and promote hyperuricemia, this study suggests that the progression from asymptomatic hyperuricemia to gout might be closely related to other genetic and/or environmental factors affecting carbohydrate metabolism and urinary urate excretion. Full article
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16 pages, 1541 KiB  
Review
Analysis of Metabolites in Gout: A Systematic Review and Meta-Analysis
by Yuanyuan Li, Xu Han, Jinlin Tong, Yuhe Wang, Xin Liu, Zeqi Liao, Miao Jiang and Hongyan Zhao
Nutrients 2023, 15(14), 3143; https://doi.org/10.3390/nu15143143 - 14 Jul 2023
Cited by 9 | Viewed by 4186
Abstract
(1) Background: Many studies have attempted to explore potential biomarkers for the early detection of gout, but consistent and high levels of evidence are lacking. In this study, metabolomics was used to summarize the changes of metabolites in the literature and explore the [...] Read more.
(1) Background: Many studies have attempted to explore potential biomarkers for the early detection of gout, but consistent and high levels of evidence are lacking. In this study, metabolomics was used to summarize the changes of metabolites in the literature and explore the potential value of metabolites in predicting the occurrence and development of gout. (2) Methods: We searched the databases including the EMBASE, the Cochrane Library, PubMed, Web of Science, VIP Date, Wanfang Data, and CNKI, and the screening was fulfilled on 30 July 2022. The records were screened according to the inclusion criteria and the risk of bias was assessed. Qualitative analysis was performed for all metabolites, and meta-analysis was performed for metabolite concentrations using random effects to calculate the Std mean difference and 95% confidence interval. (3) Results: A total of 2738 records were identified, 33 studies with 3422 participants were included, and 701 metabolites were identified. The qualitative analysis results showed that compared with the healthy control group, the concentration of 56 metabolites increased, and 22 metabolites decreased. The results of the meta-analysis indicated that 17 metabolites were statistically significant. (4) Conclusions: Metabolites are associated with gout. Some specific metabolites such as uric acid, hypoxanthine, xanthine, KYNA, guanosine, adenosine, creatinine, LB4, and DL-2-Aminoadipic acid have been highlighted in the development of gout. Full article
(This article belongs to the Section Clinical Nutrition)
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18 pages, 2715 KiB  
Article
Loss of the Kidney Urate Transporter, Urat1, Leads to Disrupted Redox Homeostasis in Mice
by Neema Jamshidi, Kabir B. Nigam and Sanjay K. Nigam
Antioxidants 2023, 12(3), 780; https://doi.org/10.3390/antiox12030780 - 22 Mar 2023
Cited by 5 | Viewed by 3626
Abstract
High uric acid is associated with gout, hypertension, metabolic syndrome, cardiovascular disease, and kidney disease. URAT1 (SLC22A12), originally discovered in mice as Rst, is generally considered a very selective uric acid transporter compared to other closely-related kidney uric acid transporters such as OAT1 [...] Read more.
High uric acid is associated with gout, hypertension, metabolic syndrome, cardiovascular disease, and kidney disease. URAT1 (SLC22A12), originally discovered in mice as Rst, is generally considered a very selective uric acid transporter compared to other closely-related kidney uric acid transporters such as OAT1 (SLC22A6, NKT) and OAT3 (SLC22A8). While the role of URAT1 in regulating human uric acid is well-established, in recent studies the gene has been linked to redox regulation in flies as well as progression of renal cell carcinoma. We have now identified over twenty metabolites in the Urat1 knockout that are generally distinct from metabolites accumulating in the Oat1 and Oat3 knockout mice, with distinct molecular properties as revealed by chemoinformatics and machine learning analysis. These metabolites are involved in seemingly disparate aspects of cellular metabolism, including pyrimidine, fatty acid, and amino acid metabolism. However, through integrative systems metabolic analysis of the transcriptomic and metabolomic data using a human metabolic reconstruction to build metabolic genome-scale models (GEMs), the cellular response to loss of Urat1/Rst revealed compensatory processes related to reactive oxygen species handling and maintaining redox state balances via Vitamin C metabolism and cofactor charging reactions. These observations are consistent with the increasingly appreciated role of the antioxidant properties of uric acid. Collectively, the results highlight the role of Urat1/Rst as a transporter strongly tied to maintaining redox homeostasis, with implications for metabolic side effects from drugs that block its function. Full article
(This article belongs to the Section Antioxidant Enzyme Systems)
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13 pages, 1288 KiB  
Review
Metabolomics in Hyperuricemia and Gout
by Rui Li, Ningning Liang, Yongzhen Tao and Huiyong Yin
Gout Urate Cryst. Depos. Dis. 2023, 1(1), 49-61; https://doi.org/10.3390/gucdd1010006 - 21 Mar 2023
Cited by 5 | Viewed by 4367
Abstract
Urate is one of the key metabolites of purine metabolism, and the overproduction of urate in the liver or decreased excretion in the kidney in humans may lead to elevated levels of urate in the circulation, termed hyperuricemia (HU). The formation of monosodium [...] Read more.
Urate is one of the key metabolites of purine metabolism, and the overproduction of urate in the liver or decreased excretion in the kidney in humans may lead to elevated levels of urate in the circulation, termed hyperuricemia (HU). The formation of monosodium urate (MSU) crystals in the joint or surrounding tissues may trigger inflammatory responses and gout attacks, which is the most common inflammatory arthritis. In addition to gout, HU has also been associated with many other metabolic diseases, such as cardiovascular disease, obesity, diabetes, fatty liver diseases, kidney diseases, hypertension, and various cancers. Overwhelming evidence indicates that HU and gout lead to systematic metabolic alterations underlying these metabolic disorders. As one of the most powerful omics techniques, metabolomics systematically analyzes all small-molecule metabolites in a biological system that directly reflect the physiological and pathological conditions. In recent years, metabolomics has been increasingly employed in clinical and experimental research in HU and gout. Emerging studies have developed predictive models to differentiate HU from gout based on metabolomics and machine-learning algorithms. In this review, we systematically summarize recent advances in metabolomic research in gout and HU in animal and human clinical studies. A comprehensive understanding of systemic metabolic changes caused by HU and gout may provide unprecedented insights into the pathological mechanisms in HU, gout, and related metabolic diseases, which may have a profound impact on the prevention, diagnosis, and treatment of HU and gout. Full article
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17 pages, 1295 KiB  
Article
Allopurinol Lowers Serum Urate but Does Not Reduce Oxidative Stress in CKD
by Mingyao Sun, Nicole Hines, Diego Scerbo, Jane Buchanan, Chaorong Wu, Patrick Ten Eyck, Diana Zepeda-Orozco, Eric B. Taylor and Diana I. Jalal
Antioxidants 2022, 11(7), 1297; https://doi.org/10.3390/antiox11071297 - 29 Jun 2022
Cited by 10 | Viewed by 3588
Abstract
Xanthine oxidase (XO) contributes to oxidative stress and vascular disease. Hyperuricemia and gout are common in patients with chronic kidney disease (CKD), a population at increased risk of vascular disease. We evaluated effects of allopurinol on serum XO activity and metabolome of CKD [...] Read more.
Xanthine oxidase (XO) contributes to oxidative stress and vascular disease. Hyperuricemia and gout are common in patients with chronic kidney disease (CKD), a population at increased risk of vascular disease. We evaluated effects of allopurinol on serum XO activity and metabolome of CKD patients who had participated in a randomized double-blind clinical trial of allopurinol vs. placebo. XO activity was measured in participants’ serum. XO expression in venous endothelial cells was evaluated via immunofluorescence. Gas chromatography mass spectrometry (GC/MS) was utilized for metabolomics analysis. We found that in patients with stage 3 CKD and hyperuricemia, allopurinol lowered serum urate while increasing serum xanthine levels. Allopurinol, however, did not significantly suppress measured serum XO activity. Of note, baseline serum XO activity was low. Additionally, neither baseline serum XO activity nor XO protein expression were associated with measures of vascular dysfunction or with systemic or endothelial biomarkers of oxidative stress. Allopurinol affected several pathways, including pentose phosphate, pyrimidine, and tyrosine metabolism. Our findings suggest that circulating XO does not contribute to vascular disease in CKD patients. In addition to inhibition of XO activity, allopurinol was observed to impact other pathways; the implications of which require further study. Full article
(This article belongs to the Topic Oxidative Stress and Inflammation)
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10 pages, 1179 KiB  
Article
Differences in Clinical and Dietary Characteristics, Serum Adipokine Levels, and Metabolomic Profiles between Early- and Late-Onset Gout
by Young Sun Suh, Hae Sook Noh, Hyun-Jin Kim, Yun-Hong Cheon, Mingyo Kim, Hanna Lee, Hyun-Ok Kim and Sang-Il Lee
Metabolites 2021, 11(6), 399; https://doi.org/10.3390/metabo11060399 - 18 Jun 2021
Cited by 7 | Viewed by 3029
Abstract
This study aimed to identify differences in clinical and dietary characteristics, serum adipokine levels, and metabolomic profiles between early- and late-onset gout. Eighty-three men with gout were divided into an early-onset group (n = 38, aged < 40 years) and a late-onset [...] Read more.
This study aimed to identify differences in clinical and dietary characteristics, serum adipokine levels, and metabolomic profiles between early- and late-onset gout. Eighty-three men with gout were divided into an early-onset group (n = 38, aged < 40 years) and a late-onset group (n = 45, aged ≥ 40 years). Dietary and clinical information was obtained at baseline. Serum adipokines, including adiponectin, resistin, leptin, and plasminogen activator inhibitor-1 (PAI-1), were quantified by a Luminex multiplex immunoassay. Metabolite expression levels in plasma were measured in 22 representative samples using metabolomics analysis based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Average body mass index, rate of consumption of sugar-sweetened beverages, and serum uric acid levels were significantly higher in the early-onset group (p < 0.05), as was the PAI-I concentration (105.01 ± 42.45 ng/mL vs. 83.76 ± 31.16 ng/mL, p = 0.013). Changes in levels of metabolites mostly involved those related to lipid metabolism. In the early-onset group, acylcarnitine analog and propylparaben levels were downregulated and negatively correlated with the PAI-1 concentration whereas LPC (22:6) and LPC (18:0) levels were upregulated and positively correlated with the PAI-1 concentration. Dietary and clinical features, serum adipokine concentrations, and metabolites differed according to whether the gout is early-onset or late-onset. The mechanisms of gout may differ between these groups and require different treatment approaches. Full article
(This article belongs to the Section Lipid Metabolism)
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19 pages, 3632 KiB  
Article
A Multi-Omics Study of Chicken Infected by Nephropathogenic Infectious Bronchitis Virus
by Puzhi Xu, Ping Liu, Changming Zhou, Yan Shi, Qingpeng Wu, Yitian Yang, Guyue Li, Guoliang Hu and Xiaoquan Guo
Viruses 2019, 11(11), 1070; https://doi.org/10.3390/v11111070 - 16 Nov 2019
Cited by 30 | Viewed by 8768
Abstract
Chicken gout resulting from nephropathogenic infectious bronchitis virus (NIBV) has become a serious kidney disease problem in chicken worldwide with alterations of the metabolic phenotypes in multiple metabolic pathways. To investigate the mechanisms in chicken responding to NIBV infection, we examined the global [...] Read more.
Chicken gout resulting from nephropathogenic infectious bronchitis virus (NIBV) has become a serious kidney disease problem in chicken worldwide with alterations of the metabolic phenotypes in multiple metabolic pathways. To investigate the mechanisms in chicken responding to NIBV infection, we examined the global transcriptomic and metabolomic profiles of the chicken’s kidney using RNA-seq and GC–TOF/MS, respectively. Furthermore, we analyzed the alterations in cecal microorganism composition in chickens using 16S rRNA-seq. Integrated analysis of these three phenotypic datasets further managed to create correlations between the altered kidney transcriptomes and metabolome, and between kidney metabolome and gut microbiome. We found that 2868 genes and 160 metabolites were deferentially expressed or accumulated in the kidney during NIBV infection processes. These genes and metabolites were linked to NIBV-infection related processes, including immune response, signal transduction, peroxisome, purine, and amino acid metabolism. In addition, the comprehensive correlations between the kidney metabolome and cecal microbial community showed contributions of gut microbiota in the progression of NIBV-infection. Taken together, our research comprehensively describes the host responses during NIBV infection and provides new clues for further dissection of specific gene functions, metabolite affections, and the role of gut microbiota during chicken gout. Full article
(This article belongs to the Section Animal Viruses)
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21 pages, 3896 KiB  
Article
Plasma Metabolic Profiling Analysis of Gout Party on Acute Gout Arthritis Rats Based on UHPLC–Q–TOF/MS Combined with Multivariate Statistical Analysis
by Yuming Wang, Chenghao Bi, Wentao Pang, Yuechen Liu, Yu Yuan, Huan Zhao, Tianpu Zhang, Yungang Zhao and Yubo Li
Int. J. Mol. Sci. 2019, 20(22), 5753; https://doi.org/10.3390/ijms20225753 - 15 Nov 2019
Cited by 36 | Viewed by 4840
Abstract
Gout Party is a Chinese medicine prescription composed of Aconiti Lateralis Radix Praeparaia, Aconiti Radix Cocta, Cremastrae Pseudobulbus Pleiones Pseudobulbus, Smilacis Glabrae Rhizoma, Rehmanniae Radix, and Glycyrrhizae Radix et Rhizoma, which can relieve joint pain caused by gouty arthritis (GA) and [...] Read more.
Gout Party is a Chinese medicine prescription composed of Aconiti Lateralis Radix Praeparaia, Aconiti Radix Cocta, Cremastrae Pseudobulbus Pleiones Pseudobulbus, Smilacis Glabrae Rhizoma, Rehmanniae Radix, and Glycyrrhizae Radix et Rhizoma, which can relieve joint pain caused by gouty arthritis (GA) and rheumatoid, and has a therapeutic effect on acute gouty arthritis (AGA). However, little information is available on the molecular biological basis and therapeutic mechanism of Gout Party for the treatment of AGA. AGA model was established by injecting sodium urate, and colchicine served as a positive control drug. We established a metabolomic method based on ultra-high-performance liquid chromatography–tandem quadrupole/time-of-flight mass spectrometry (UHPLC–Q–TOF/MS) to analyze the plasma samples of model group rats and blank group rats. Multiple statistical analyses, including principal component analysis (PCA) and partial least square discrimination analysis (PLS-DA), were used to examine metabolite profile changes in plasma samples. Finally, we identified 2–ketobutyric acid, 3–hexenedioic acid, but–2–enoic acid, and so on; 22 endogenous metabolites associated with AGA. After successful molding, we found that 2–ketobutyric acid, 3–hexenedioic acid, but–2–enoic acid, argininic acid, galactonic acid, lactic acid, equol 4′–O–glucuronide, deoxycholic acid glycine conjugate, glycocholic acid, sphinganine 1–phosphate, LPE (0:0/20:3), LPE (0:0/16:0), LPC (15:0) decreased significantly (p < 0.05 or p < 0.01), alanine, erythrulose, 3–dehydrocarnitine, m–methylhippuric acid, 3–hydroxyoctanoic acid, p–cresol sulfate, estriol 3–sulfate 16–glucuronide, 10–hydroxy–9–(phosphonooxy)octadecenoate, docosahexaenoic acid increased significantly (p < 0.05 or p < 0.01). After Gout Party treatment, 14 biomarkers had a tendency to normal conditions. These above biomarkers were mainly involved in fatty acid metabolism, bile acid metabolism, amino acid metabolism, and energy metabolism pathways. These results suggested that Gout Party exerted therapeutic effects of treating AGA by improving energy metabolism disorder and amino acid metabolism dysfunction, and attenuating fatty acid metabolism abnormal and inflammation. The results of this experiment provided a reference for revealing the metabolic mechanism produced by Gout Party in the treatment of AGA, but the subsequent studies need to be further improved and supported by relevant cell experiments and clinical experiments. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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13 pages, 1850 KiB  
Article
Comparative Metabolite Profiling of Triterpenoid Saponins and Flavonoids in Flower Color Mutations of Primula veris L.
by Lysanne Apel, Dietmar R. Kammerer, Florian C. Stintzing and Otmar Spring
Int. J. Mol. Sci. 2017, 18(1), 153; https://doi.org/10.3390/ijms18010153 - 13 Jan 2017
Cited by 38 | Viewed by 11056
Abstract
Primula veris L. is an important medicinal plant with documented use for the treatment of gout, headache and migraine reaching back to the Middle Ages. Triterpenoid saponins from roots and flowers are used in up-to-date phytotherapeutic treatment of bronchitis and colds due to [...] Read more.
Primula veris L. is an important medicinal plant with documented use for the treatment of gout, headache and migraine reaching back to the Middle Ages. Triterpenoid saponins from roots and flowers are used in up-to-date phytotherapeutic treatment of bronchitis and colds due to their expectorant and secretolytic effects. In addition to the wild type plants with yellow petals, a red variant and an intermediate orange form of Primula veris L. have recently been found in a natural habitat. The secondary metabolite profiles of roots, leaves and flowers of these rare variants were investigated and compared with the wild type metabolome. Two flavonoids, six flavonoid glycosides, four novel methylated flavonoid glycosides, five anthocyanins and three triterpenoid saponins were identified in alcoholic extracts from the petals, leaves and roots of the three variants by high performance liquid chromatography (HPLC)-diode array detection (DAD)/mass spectrometry (MSn) analyses. Anthocyanins were detected in the petals of the red and orange variety, but not in the wild type. No other effects on the metabolite profiles of the three varieties have been observed. The possibility is discussed that a regulatory step of the anthocyanin biosynthetic pathway may have been affected by mutation thus triggering color polymorphism in the petals. Full article
(This article belongs to the Special Issue Metabolomics in the Plant Sciences)
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