Yuanfeng Huang, Mingjie Liang, Yiwen Liao, Zirui Ji, Wanfen Lin, Xiangjin Pu, Lexun Wang, Weixuan Wang
This study focused on exploring the effects of SW033291, an inhibitor of 15-hydroxyprostaglandin dehydrogenase, on type 2 diabetes mellitus (T2DM) mice from a comprehensive perspective. Studies have demonstrated that SW033291 benefits tissue repair, organ function, and muscle mass in elderly mice. Our recent investigation initially reported the beneficial effect of SW033291 on T2DM progression. Herein, we used a T2DM mouse model induced by a high-fat diet and streptozotocin injection. Then, serum and liver metabolomics, as well as liver transcriptomic analyses, were performed to provide a systematic perspective of the SW033291-ameliorated T2DM. The results indicate SW033291 improved T2DM by regulating steroid hormone biosynthesis and linoleic/arachidonic acid metabolism. Furthermore, integrated transcriptomic and metabolomic analyses suggested that key genes and metabolites such as Cyp2c55, Cyp3a11, Cyp21a1, Myc, Gstm1, Gstm3, 9,10-dihydroxyoctadecenoic acid, 11-dehydrocorticosterone, and 12,13-dihydroxy-9Z-octadecenoic acid played crucial roles in these pathways. qPCR analysis validated the significant decreases in the hepatic gene expressions of Cyp2c55, Cyp3a11, Myc, Gstm1, and Gstm3 in the T2DM mice, which were reversed following SW033291 treatment. Meanwhile, the elevated mRNA level of Cyp21a1 in T2DM mice was decreased after SW033291 administration. Taken together, our findings suggest that SW033291 has promising potential in alleviating T2DM and could be a novel therapeutic candidate.
{"title":"Investigating the Mechanisms of 15-PGDH Inhibitor SW033291 in Improving Type 2 Diabetes Mellitus: Insights from Metabolomics and Transcriptomics.","authors":"Yuanfeng Huang, Mingjie Liang, Yiwen Liao, Zirui Ji, Wanfen Lin, Xiangjin Pu, Lexun Wang, Weixuan Wang","doi":"10.3390/metabo14090509","DOIUrl":"https://doi.org/10.3390/metabo14090509","url":null,"abstract":"<p><p>This study focused on exploring the effects of SW033291, an inhibitor of 15-hydroxyprostaglandin dehydrogenase, on type 2 diabetes mellitus (T2DM) mice from a comprehensive perspective. Studies have demonstrated that SW033291 benefits tissue repair, organ function, and muscle mass in elderly mice. Our recent investigation initially reported the beneficial effect of SW033291 on T2DM progression. Herein, we used a T2DM mouse model induced by a high-fat diet and streptozotocin injection. Then, serum and liver metabolomics, as well as liver transcriptomic analyses, were performed to provide a systematic perspective of the SW033291-ameliorated T2DM. The results indicate SW033291 improved T2DM by regulating steroid hormone biosynthesis and linoleic/arachidonic acid metabolism. Furthermore, integrated transcriptomic and metabolomic analyses suggested that key genes and metabolites such as <i>Cyp2c55</i>, <i>Cyp3a11</i>, <i>Cyp21a1</i>, <i>Myc</i>, <i>Gstm1</i>, <i>Gstm3</i>, 9,10-dihydroxyoctadecenoic acid, 11-dehydrocorticosterone, and 12,13-dihydroxy-9Z-octadecenoic acid played crucial roles in these pathways. qPCR analysis validated the significant decreases in the hepatic gene expressions of <i>Cyp2c55</i>, <i>Cyp3a11</i>, <i>Myc</i>, <i>Gstm1</i>, and <i>Gstm3</i> in the T2DM mice, which were reversed following SW033291 treatment. Meanwhile, the elevated mRNA level of <i>Cyp21a1</i> in T2DM mice was decreased after SW033291 administration. Taken together, our findings suggest that SW033291 has promising potential in alleviating T2DM and could be a novel therapeutic candidate.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"14 9","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11434390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142349779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Caroline Brito Nunes, Maria Carolina Borges, Rachel M Freathy, Deborah A Lawlor, Elisabeth Qvigstad, David M Evans, Gunn-Helen Moen
Background/Objectives: During pregnancy, physiological changes in maternal circulating glucose levels and its metabolism are essential to meet maternal and fetal energy demands. Major changes in glucose metabolism occur throughout pregnancy and consist of higher insulin resistance and a compensatory increase in insulin secretion to maintain glucose homeostasis. For some women, this change is insufficient to maintain normoglycemia, leading to gestational diabetes mellitus (GDM), a condition characterized by maternal glucose intolerance and hyperglycaemia first diagnosed during the second or third trimester of pregnancy. GDM is diagnosed in approximately 14.0% of pregnancies globally, and it is often associated with short- and long-term adverse health outcomes in both mothers and offspring. Although recent studies have highlighted the role of genetic determinants in the development of GDM, research in this area is still lacking, hindering the development of prevention and treatment strategies. Methods: In this paper, we review recent advances in the understanding of genetic determinants of GDM and glycaemic traits during pregnancy. Results/Conclusions: Our review highlights the need for further collaborative efforts as well as larger and more diverse genotyped pregnancy cohorts to deepen our understanding of the genetic aetiology of GDM, address research gaps, and further improve diagnostic and treatment strategies.
{"title":"Understanding the Genetic Landscape of Gestational Diabetes: Insights into the Causes and Consequences of Elevated Glucose Levels in Pregnancy.","authors":"Caroline Brito Nunes, Maria Carolina Borges, Rachel M Freathy, Deborah A Lawlor, Elisabeth Qvigstad, David M Evans, Gunn-Helen Moen","doi":"10.3390/metabo14090508","DOIUrl":"https://doi.org/10.3390/metabo14090508","url":null,"abstract":"<p><p><b>Background/Objectives:</b> During pregnancy, physiological changes in maternal circulating glucose levels and its metabolism are essential to meet maternal and fetal energy demands. Major changes in glucose metabolism occur throughout pregnancy and consist of higher insulin resistance and a compensatory increase in insulin secretion to maintain glucose homeostasis. For some women, this change is insufficient to maintain normoglycemia, leading to gestational diabetes mellitus (GDM), a condition characterized by maternal glucose intolerance and hyperglycaemia first diagnosed during the second or third trimester of pregnancy. GDM is diagnosed in approximately 14.0% of pregnancies globally, and it is often associated with short- and long-term adverse health outcomes in both mothers and offspring. Although recent studies have highlighted the role of genetic determinants in the development of GDM, research in this area is still lacking, hindering the development of prevention and treatment strategies. <b>Methods:</b> In this paper, we review recent advances in the understanding of genetic determinants of GDM and glycaemic traits during pregnancy. <b>Results/Conclusions:</b> Our review highlights the need for further collaborative efforts as well as larger and more diverse genotyped pregnancy cohorts to deepen our understanding of the genetic aetiology of GDM, address research gaps, and further improve diagnostic and treatment strategies.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"14 9","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11434570/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142349785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Prince Sellase Gameli, Johannes Kutzler, Diletta Berardinelli, Jeremy Carlier, Volker Auwärter, Francesco Paolo Busardò
Background: The abuse of psychoactive substances presents challenges in clinical and forensic toxicology. The emergence of novel and potent drugs that pose significant health risks, in particular towards frequent abusers and users unaware of the ingredients, further complicates the situation. Designer benzodiazepines have become a fast-growing subgroup of these new psychoactive substances (NPSs), and their overdose may potentially turn fatal, especially when combined with other central nervous system depressants. In 2021, flubrotizolam, a potent thieno-triazolo designer benzodiazepine, emerged on the illicit market, available online as a "research chemical". The identification of markers of consumption for this designer benzodiazepine is essential in analytical toxicology, especially in clinical and forensic cases.
Methods: We therefore aimed to identify biomarkers of flubrotizolam uptake in ten-donor-pooled human hepatocytes, applying liquid chromatography high-resolution mass spectrometry and software-aided data mining supported by in silico prediction tools.
Results: Prediction studies resulted in 10 and 13 first- and second-generation metabolites, respectively, mainly transformed through hydroxylation and sulfation, methylation, and glucuronidation reactions. We identified six metabolites after 3 h human hepatocyte incubation: two hydroxylated metabolites (α- and 6-hydroxy-flubrotizolam), two 6-hydroxy-glucuronides, a reduced-hydroxy-N-glucuronide, and an N-glucuronide.
Conclusions: We suggest detecting flubrotizolam and its hydroxylated metabolites as markers of consumption after the glucuronide hydrolysis of biological samples. The results are consistent with the in vivo metabolism of brotizolam, a medically used benzodiazepine and a chloro-phenyl analog of flubrotizolam.
{"title":"Exploring the Metabolism of Flubrotizolam, a Potent Thieno-Triazolo Diazepine, Using Human Hepatocytes and High-Resolution Mass Spectrometry.","authors":"Prince Sellase Gameli, Johannes Kutzler, Diletta Berardinelli, Jeremy Carlier, Volker Auwärter, Francesco Paolo Busardò","doi":"10.3390/metabo14090506","DOIUrl":"https://doi.org/10.3390/metabo14090506","url":null,"abstract":"<p><strong>Background: </strong>The abuse of psychoactive substances presents challenges in clinical and forensic toxicology. The emergence of novel and potent drugs that pose significant health risks, in particular towards frequent abusers and users unaware of the ingredients, further complicates the situation. Designer benzodiazepines have become a fast-growing subgroup of these new psychoactive substances (NPSs), and their overdose may potentially turn fatal, especially when combined with other central nervous system depressants. In 2021, flubrotizolam, a potent thieno-triazolo designer benzodiazepine, emerged on the illicit market, available online as a \"research chemical\". The identification of markers of consumption for this designer benzodiazepine is essential in analytical toxicology, especially in clinical and forensic cases.</p><p><strong>Methods: </strong>We therefore aimed to identify biomarkers of flubrotizolam uptake in ten-donor-pooled human hepatocytes, applying liquid chromatography high-resolution mass spectrometry and software-aided data mining supported by in silico prediction tools.</p><p><strong>Results: </strong>Prediction studies resulted in 10 and 13 first- and second-generation metabolites, respectively, mainly transformed through hydroxylation and sulfation, methylation, and glucuronidation reactions. We identified six metabolites after 3 h human hepatocyte incubation: two hydroxylated metabolites (α- and 6-hydroxy-flubrotizolam), two 6-hydroxy-glucuronides, a reduced-hydroxy-<i>N</i>-glucuronide, and an <i>N</i>-glucuronide.</p><p><strong>Conclusions: </strong>We suggest detecting flubrotizolam and its hydroxylated metabolites as markers of consumption after the glucuronide hydrolysis of biological samples. The results are consistent with the in vivo metabolism of brotizolam, a medically used benzodiazepine and a chloro-phenyl analog of flubrotizolam.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"14 9","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11433749/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142349778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ya Gao, Rebecca Finlay, Xiaofei Yin, Lorraine Brennan
Introduction There is increasing interest in food biomarkers to address the shortcomings of self-reported dietary assessments. Berries are regarded as important fruits worldwide; however, there are no well-validated biomarkers of berry intake. Thus, the objective of this study is to identify urinary biomarkers of berry intake. Methods For the discovery study, participants consumed 192 g strawberries with 150 g blueberries, and urine samples were collected at 2, 4, 6, and 24 h post-consumption. A dose–response study was performed, whereby participants consumed three portions (78 g, 278 g, and 428 g) of mixed strawberries and blueberries. The urine samples were profiled by an untargeted LC-MS metabolomics approach in the positive and negative modes. Results Statistical analysis of the data revealed that 39 features in the negative mode and 15 in the positive mode significantly increased between fasting and 4 h following mixed berry intake. Following the analysis of the dose–response data, 21 biomarkers showed overall significance across the portions of berry intake. Identification of the biomarkers was performed using fragmentation matches in the METLIN, HMDB, and MoNA databases and in published papers, confirmed where possible with authentic standards. Conclusions The ability of the panel of biomarkers to assess intake was examined, and the predictability was good, laying the foundations for the development of biomarker panels.
{"title":"Urinary Biomarkers of Strawberry and Blueberry Intake","authors":"Ya Gao, Rebecca Finlay, Xiaofei Yin, Lorraine Brennan","doi":"10.3390/metabo14090505","DOIUrl":"https://doi.org/10.3390/metabo14090505","url":null,"abstract":"Introduction There is increasing interest in food biomarkers to address the shortcomings of self-reported dietary assessments. Berries are regarded as important fruits worldwide; however, there are no well-validated biomarkers of berry intake. Thus, the objective of this study is to identify urinary biomarkers of berry intake. Methods For the discovery study, participants consumed 192 g strawberries with 150 g blueberries, and urine samples were collected at 2, 4, 6, and 24 h post-consumption. A dose–response study was performed, whereby participants consumed three portions (78 g, 278 g, and 428 g) of mixed strawberries and blueberries. The urine samples were profiled by an untargeted LC-MS metabolomics approach in the positive and negative modes. Results Statistical analysis of the data revealed that 39 features in the negative mode and 15 in the positive mode significantly increased between fasting and 4 h following mixed berry intake. Following the analysis of the dose–response data, 21 biomarkers showed overall significance across the portions of berry intake. Identification of the biomarkers was performed using fragmentation matches in the METLIN, HMDB, and MoNA databases and in published papers, confirmed where possible with authentic standards. Conclusions The ability of the panel of biomarkers to assess intake was examined, and the predictability was good, laying the foundations for the development of biomarker panels.","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"77 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mariana Luna, Silvia Pereira, Carlos Saboya, Andrea Ramalho
The factors determining the reversal of metabolically unhealthy obesity (MUO) to metabolically healthy obesity (MHO) after Roux-en-Y gastric bypass (RYGB) are not completely elucidated. The present study aims to evaluate body adiposity and distribution, through different indices, according to metabolic phenotypes before and 6 months after RYGB, and the relationship between these indices and transition from MUO to MHO. This study reports a prospective longitudinal study on adults with obesity who were evaluated before (T0) and 6 months (T1) after RYGB. Bodyweight, height, waist circumference (WC), BMI, waist-to-height ratio (WHR), total cholesterol (TC), HDL-c, LDL-c, triglycerides, insulin, glucose, HbA1c and HOMA-IR were evaluated. The visceral adiposity index (VAI), the conicity index (CI), the lipid accumulation product (LAP), CUN-BAE and body shape index (ABSI) were calculated. MUO was classified based on insulin resistance. MUO at T0 with transition to MHO at T1 formed the MHO-t group MHO and MUO at both T0 and T1 formed the MHO-m and MUO-m groups, respectively. At T0, 37.3% of the 62 individuals were classified as MHO and 62.7% as MUO. Individuals in the MUO-T0 group had higher blood glucose, HbA1c, HOMA-IR, insulin, TC and LDL-c compared to those in the MHO-T0 group. Both groups showed significant improvement in biochemical and body variables at T1. After RYGB, 89.2% of MUO-T0 became MHO (MHO-t). The MUO-m group presented higher HOMA-IR, insulin and VAI, compared to the MHO-m and MHO-t groups. CI and ABSI at T0 correlated with HOMA-IR at T1 in the MHO-t and MHO-m groups. CI and ABSI, indicators of visceral fat, are promising for predicting post-RYGB metabolic improvement. Additional studies are needed to confirm the sustainability of MUO reversion and its relationship with these indices.
{"title":"Relationship between Body Adiposity Indices and Reversal of Metabolically Unhealthy Obesity 6 Months after Roux-en-Y Gastric Bypass","authors":"Mariana Luna, Silvia Pereira, Carlos Saboya, Andrea Ramalho","doi":"10.3390/metabo14090502","DOIUrl":"https://doi.org/10.3390/metabo14090502","url":null,"abstract":"The factors determining the reversal of metabolically unhealthy obesity (MUO) to metabolically healthy obesity (MHO) after Roux-en-Y gastric bypass (RYGB) are not completely elucidated. The present study aims to evaluate body adiposity and distribution, through different indices, according to metabolic phenotypes before and 6 months after RYGB, and the relationship between these indices and transition from MUO to MHO. This study reports a prospective longitudinal study on adults with obesity who were evaluated before (T0) and 6 months (T1) after RYGB. Bodyweight, height, waist circumference (WC), BMI, waist-to-height ratio (WHR), total cholesterol (TC), HDL-c, LDL-c, triglycerides, insulin, glucose, HbA1c and HOMA-IR were evaluated. The visceral adiposity index (VAI), the conicity index (CI), the lipid accumulation product (LAP), CUN-BAE and body shape index (ABSI) were calculated. MUO was classified based on insulin resistance. MUO at T0 with transition to MHO at T1 formed the MHO-t group MHO and MUO at both T0 and T1 formed the MHO-m and MUO-m groups, respectively. At T0, 37.3% of the 62 individuals were classified as MHO and 62.7% as MUO. Individuals in the MUO-T0 group had higher blood glucose, HbA1c, HOMA-IR, insulin, TC and LDL-c compared to those in the MHO-T0 group. Both groups showed significant improvement in biochemical and body variables at T1. After RYGB, 89.2% of MUO-T0 became MHO (MHO-t). The MUO-m group presented higher HOMA-IR, insulin and VAI, compared to the MHO-m and MHO-t groups. CI and ABSI at T0 correlated with HOMA-IR at T1 in the MHO-t and MHO-m groups. CI and ABSI, indicators of visceral fat, are promising for predicting post-RYGB metabolic improvement. Additional studies are needed to confirm the sustainability of MUO reversion and its relationship with these indices.","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"16 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Microplastics are emerging pollutants that have garnered significant attention, with evidence suggesting their association with the pathogenesis of type 2 diabetes mellitus. In order to assess the impact of polystyrene microplastic exposure on alterations in the gut microbiota and the subsequent implications for glucose dysregulation under different dietary conditions in mice, we investigated the effects and disparities in the blood glucose levels induced by polystyrene microplastic exposure in mice fed a high-fat diet versus those fed a normal diet. Using 16S rRNA sequencing and bioinformatics analyses, we explored the dynamic changes and discrepancies in the gut microbiota stability induced by polystyrene microplastic exposure under varied dietary conditions, and we screened for gut genera associated with the potential of polystyrene microplastics to disrupt glucose homeostasis. Our findings indicate that a high-fat diet resulted in abnormal mouse body weight, energy intake, blood glucose levels and related metabolic parameters. Additionally, polystyrene microplastic exposure exacerbated the glucose metabolism disorders induced by a high-fat diet. Furthermore, the composition and diversity of the mouse gut microbiota were significantly altered following microplastic exposure, with 11 gut genera exhibiting a differential presence between mice fed a high-fat diet combined with microplastic exposure compared to those fed a normal diet with microplastic exposure. Moreover, Ucg-009 played an intermediary role in the association between a high-fat diet and the fasting blood glucose. Hence, our study demonstrates that polystyrene microplastic exposure exacerbates high-fat diet-induced glucose metabolism disorders, whereas its impact on the blood glucose under normal dietary conditions is not significant, highlighting the differential influence attributable to distinct alterations in characteristic gut genera.
{"title":"Impact of Microplastic Exposure on Blood Glucose Levels and Gut Microbiota: Differential Effects under Normal or High-Fat Diet Conditions","authors":"Manjin Xu, Huixia Niu, Lizhi Wu, Mingluan Xing, Zhe Mo, Zhijian Chen, Xueqing Li, Xiaoming Lou","doi":"10.3390/metabo14090504","DOIUrl":"https://doi.org/10.3390/metabo14090504","url":null,"abstract":"Microplastics are emerging pollutants that have garnered significant attention, with evidence suggesting their association with the pathogenesis of type 2 diabetes mellitus. In order to assess the impact of polystyrene microplastic exposure on alterations in the gut microbiota and the subsequent implications for glucose dysregulation under different dietary conditions in mice, we investigated the effects and disparities in the blood glucose levels induced by polystyrene microplastic exposure in mice fed a high-fat diet versus those fed a normal diet. Using 16S rRNA sequencing and bioinformatics analyses, we explored the dynamic changes and discrepancies in the gut microbiota stability induced by polystyrene microplastic exposure under varied dietary conditions, and we screened for gut genera associated with the potential of polystyrene microplastics to disrupt glucose homeostasis. Our findings indicate that a high-fat diet resulted in abnormal mouse body weight, energy intake, blood glucose levels and related metabolic parameters. Additionally, polystyrene microplastic exposure exacerbated the glucose metabolism disorders induced by a high-fat diet. Furthermore, the composition and diversity of the mouse gut microbiota were significantly altered following microplastic exposure, with 11 gut genera exhibiting a differential presence between mice fed a high-fat diet combined with microplastic exposure compared to those fed a normal diet with microplastic exposure. Moreover, Ucg-009 played an intermediary role in the association between a high-fat diet and the fasting blood glucose. Hence, our study demonstrates that polystyrene microplastic exposure exacerbates high-fat diet-induced glucose metabolism disorders, whereas its impact on the blood glucose under normal dietary conditions is not significant, highlighting the differential influence attributable to distinct alterations in characteristic gut genera.","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"32 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Backgrounds: Sinojackia xylocarpa Hu is a deciduous tree in the Styracaceae family, and it is classified as a Class II endangered plant in China. Seed storage technology is an effective means of conserving germplasm resources, but the effects of different storage conditions on the quality and associated metabolism of S. xylocarpa seeds remain unclear. This study analyzed the physiological and metabolic characteristics of S. xylocarpa seeds under four storage conditions. Results: Our findings demonstrate that reducing seed moisture content and storage temperature effectively prolongs storage life. Seeds stored under that condition exhibited higher internal nutrient levels, lower endogenous abscisic acid (ABA) hormone levels, and elevated gibberellic acid (GA3) levels. Additionally, 335 metabolites were identified under four different storage conditions. The analysis indicates that S. xylocarpa seeds extend seed longevity and maintain cellular structural stability mainly by regulating the changes in metabolites related to lipid, amino acid, carbohydrate, and carotenoid metabolic pathways under the storage conditions of a low temperature and low seed moisture. Conclusions: These findings provide new insights at the physiological and metabolic levels into how these storage conditions extend seed longevity while also offering effective storage strategies for preserving the germplasm resources of S. xylocarpa.
{"title":"Metabolomic and Physiological Analyses Reveal the Effects of Different Storage Conditions on Sinojackia xylocarpa Hu Seeds","authors":"Hao Cai, Yongbao Shen","doi":"10.3390/metabo14090503","DOIUrl":"https://doi.org/10.3390/metabo14090503","url":null,"abstract":"Backgrounds: Sinojackia xylocarpa Hu is a deciduous tree in the Styracaceae family, and it is classified as a Class II endangered plant in China. Seed storage technology is an effective means of conserving germplasm resources, but the effects of different storage conditions on the quality and associated metabolism of S. xylocarpa seeds remain unclear. This study analyzed the physiological and metabolic characteristics of S. xylocarpa seeds under four storage conditions. Results: Our findings demonstrate that reducing seed moisture content and storage temperature effectively prolongs storage life. Seeds stored under that condition exhibited higher internal nutrient levels, lower endogenous abscisic acid (ABA) hormone levels, and elevated gibberellic acid (GA3) levels. Additionally, 335 metabolites were identified under four different storage conditions. The analysis indicates that S. xylocarpa seeds extend seed longevity and maintain cellular structural stability mainly by regulating the changes in metabolites related to lipid, amino acid, carbohydrate, and carotenoid metabolic pathways under the storage conditions of a low temperature and low seed moisture. Conclusions: These findings provide new insights at the physiological and metabolic levels into how these storage conditions extend seed longevity while also offering effective storage strategies for preserving the germplasm resources of S. xylocarpa.","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"10 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Assim A. Alfadda, Anas M. Abdel Rahman, Hicham Benabdelkamel, Reem AlMalki, Bashayr Alsuwayni, Abdulaziz Alhossan, Madhawi M. Aldhwayan, Ghalia N. Abdeen, Alexander Dimitri Miras, Afshan Masood
Background: Liraglutide, a long-acting glucagon-like peptide-1 receptor agonist (GLP1RA), is a well-established anti-diabetic drug, has also been approved for the treatment of obesity at a dose of 3 mg. There are a limited number of studies in the literature that have looked at changes in metabolite levels before and after liraglutide treatment in patients with obesity. To this end, in the present study we aimed to explore the changes in the plasma metabolomic profile, using liquid chromatography-high resolution mass spectrometry (LC-HRMS) in patients with obesity. Methods: A single-center prospective study was undertaken to evaluate the effectiveness of 3 mg liraglutide therapy in twenty-three patients (M/F: 8/15) with obesity, mean BMI 40.81 ± 5.04 kg/m2, and mean age of 36 ± 10.9 years, in two groups: at baseline (pre-treatment) and after 12 weeks of treatment (post-treatment). An untargeted metabolomic profiling was conducted in plasma from the pre-treatment and post-treatment groups using LC-HRMS, along with bioinformatics analysis using ingenuity pathway analysis (IPA). Results: The metabolomics analysis revealed a significant (FDR p-value ≤ 0.05, FC 1.5) dysregulation of 161 endogenous metabolites (97 upregulated and 64 downregulated) with distinct separation between the two groups. Among the significantly dysregulated metabolites, the majority of them were identified as belonging to the class of oxidized lipids (oxylipins) that includes arachidonic acid and its derivatives, phosphorglycerophosphates, N-acylated amino acids, steroid hormones, and bile acids. The biomarker analysis conducted using MetaboAnalyst showed PGP (a21:0/PG/F1alpha), an oxidized lipid, as the first metabolite among the list of the top 15 biomarkers, followed by cysteine and estrone. The IPA analysis showed that the dysregulated metabolites impacted the pathway related to cell signaling, free radical scavenging, and molecular transport, and were focused around the dysregulation of NF-κB, ERK, MAPK, PKc, VEGF, insulin, and pro-inflammatory cytokine signaling pathways. Conclusions: The findings suggest that liraglutide treatment reduces inflammation and modulates lipid metabolism and oxidative stress. Our study contributes to a better understanding of the drug’s multifaceted impact on overall metabolism in patients with obesity.
{"title":"Metabolomic Effects of Liraglutide Therapy on the Plasma Metabolomic Profile of Patients with Obesity","authors":"Assim A. Alfadda, Anas M. Abdel Rahman, Hicham Benabdelkamel, Reem AlMalki, Bashayr Alsuwayni, Abdulaziz Alhossan, Madhawi M. Aldhwayan, Ghalia N. Abdeen, Alexander Dimitri Miras, Afshan Masood","doi":"10.3390/metabo14090500","DOIUrl":"https://doi.org/10.3390/metabo14090500","url":null,"abstract":"Background: Liraglutide, a long-acting glucagon-like peptide-1 receptor agonist (GLP1RA), is a well-established anti-diabetic drug, has also been approved for the treatment of obesity at a dose of 3 mg. There are a limited number of studies in the literature that have looked at changes in metabolite levels before and after liraglutide treatment in patients with obesity. To this end, in the present study we aimed to explore the changes in the plasma metabolomic profile, using liquid chromatography-high resolution mass spectrometry (LC-HRMS) in patients with obesity. Methods: A single-center prospective study was undertaken to evaluate the effectiveness of 3 mg liraglutide therapy in twenty-three patients (M/F: 8/15) with obesity, mean BMI 40.81 ± 5.04 kg/m2, and mean age of 36 ± 10.9 years, in two groups: at baseline (pre-treatment) and after 12 weeks of treatment (post-treatment). An untargeted metabolomic profiling was conducted in plasma from the pre-treatment and post-treatment groups using LC-HRMS, along with bioinformatics analysis using ingenuity pathway analysis (IPA). Results: The metabolomics analysis revealed a significant (FDR p-value ≤ 0.05, FC 1.5) dysregulation of 161 endogenous metabolites (97 upregulated and 64 downregulated) with distinct separation between the two groups. Among the significantly dysregulated metabolites, the majority of them were identified as belonging to the class of oxidized lipids (oxylipins) that includes arachidonic acid and its derivatives, phosphorglycerophosphates, N-acylated amino acids, steroid hormones, and bile acids. The biomarker analysis conducted using MetaboAnalyst showed PGP (a21:0/PG/F1alpha), an oxidized lipid, as the first metabolite among the list of the top 15 biomarkers, followed by cysteine and estrone. The IPA analysis showed that the dysregulated metabolites impacted the pathway related to cell signaling, free radical scavenging, and molecular transport, and were focused around the dysregulation of NF-κB, ERK, MAPK, PKc, VEGF, insulin, and pro-inflammatory cytokine signaling pathways. Conclusions: The findings suggest that liraglutide treatment reduces inflammation and modulates lipid metabolism and oxidative stress. Our study contributes to a better understanding of the drug’s multifaceted impact on overall metabolism in patients with obesity.","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"98 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vidhi Kulkarni, Igor F. Tsigelny, Valentina L. Kouznetsova
Background: Feline mammary carcinoma (FMC) is a prevalent and fatal carcinoma that predominantly affects unspayed female cats. FMC is the third most common carcinoma in cats but is still underrepresented in research. Current diagnosis methods include physical examinations, imaging tests, and fine-needle aspiration. The diagnosis through these methods is sometimes delayed and unreliable, leading to increased chances of mortality. Objectives: The objective of this study was to identify the biomarkers, including blood metabolites and genes, related to feline mammary carcinoma, study their relationships, and develop a machine learning (ML) model for the early diagnosis of the disease. Methods: We analyzed the blood metabolites of felines with mammary carcinoma using the pathway analysis feature in MetaboAnalyst software, v. 5.0. We utilized machine-learning (ML) methods to recognize FMC using the blood metabolites of sick patients. Results: The metabolic pathways that were elucidated to be associated with this disease include alanine, aspartate and glutamate metabolism, Glutamine and glutamate metabolism, Arginine biosynthesis, and Glycerophospholipid metabolism. Furthermore, we also elucidated several genes that play a significant role in the development of FMC, such as ERBB2, PDGFA, EGFR, FLT4, ERBB3, FIGF, PDGFC, PDGFB through STRINGdb, a database of known and predicted protein-protein interactions, and MetaboAnalyst 5.0. The best-performing ML model was able to predict metabolite class with an accuracy of 85.11%. Conclusion: Our findings demonstrate that the identification of the biomarkers associated with FMC and the affected metabolic pathways can aid in the early diagnosis of feline mammary carcinoma.
背景：猫乳腺癌（FMC）是一种常见的致命癌症，主要影响未绝育的雌猫。FMC 是猫科动物中第三大最常见的癌症，但在研究中的代表性仍然不足。目前的诊断方法包括体格检查、成像测试和细针穿刺。这些方法有时会延误诊断且不可靠，导致死亡率上升。研究目的本研究的目的是确定与猫乳腺癌相关的生物标志物，包括血液代谢物和基因，研究它们之间的关系，并开发一个用于疾病早期诊断的机器学习（ML）模型。研究方法我们使用 MetaboAnalyst 软件 5.0 版的通路分析功能分析了患乳腺癌猫科动物的血液代谢物。我们利用机器学习（ML）方法来识别患病猫科动物的血液代谢物。结果阐明了与该疾病相关的代谢途径，包括丙氨酸、天门冬氨酸和谷氨酸代谢、谷氨酰胺和谷氨酸代谢、精氨酸生物合成和甘油磷脂代谢。此外，我们还通过STRINGdb（一个已知和预测的蛋白质-蛋白质相互作用数据库）和MetaboAnalyst 5.0阐明了在FMC发病中起重要作用的几个基因，如ERBB2、PDGFA、表皮生长因子受体、FLT4、ERBB3、FIGF、PDGFC、PDGFB。表现最好的 ML 模型预测代谢物类别的准确率为 85.11%。结论我们的研究结果表明，识别与猫乳腺癌相关的生物标记物以及受影响的代谢途径有助于猫乳腺癌的早期诊断。
{"title":"Implementation of Machine Learning-Based System for Early Diagnosis of Feline Mammary Carcinomas through Blood Metabolite Profiling","authors":"Vidhi Kulkarni, Igor F. Tsigelny, Valentina L. Kouznetsova","doi":"10.3390/metabo14090501","DOIUrl":"https://doi.org/10.3390/metabo14090501","url":null,"abstract":"Background: Feline mammary carcinoma (FMC) is a prevalent and fatal carcinoma that predominantly affects unspayed female cats. FMC is the third most common carcinoma in cats but is still underrepresented in research. Current diagnosis methods include physical examinations, imaging tests, and fine-needle aspiration. The diagnosis through these methods is sometimes delayed and unreliable, leading to increased chances of mortality. Objectives: The objective of this study was to identify the biomarkers, including blood metabolites and genes, related to feline mammary carcinoma, study their relationships, and develop a machine learning (ML) model for the early diagnosis of the disease. Methods: We analyzed the blood metabolites of felines with mammary carcinoma using the pathway analysis feature in MetaboAnalyst software, v. 5.0. We utilized machine-learning (ML) methods to recognize FMC using the blood metabolites of sick patients. Results: The metabolic pathways that were elucidated to be associated with this disease include alanine, aspartate and glutamate metabolism, Glutamine and glutamate metabolism, Arginine biosynthesis, and Glycerophospholipid metabolism. Furthermore, we also elucidated several genes that play a significant role in the development of FMC, such as ERBB2, PDGFA, EGFR, FLT4, ERBB3, FIGF, PDGFC, PDGFB through STRINGdb, a database of known and predicted protein-protein interactions, and MetaboAnalyst 5.0. The best-performing ML model was able to predict metabolite class with an accuracy of 85.11%. Conclusion: Our findings demonstrate that the identification of the biomarkers associated with FMC and the affected metabolic pathways can aid in the early diagnosis of feline mammary carcinoma.","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"49 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142266772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amar Kumar, Joshua Tatarian, Valentina Shakhnovich, Rachel L. Chevalier, Marc Sudman, Daniel J. Lovell, Susan D. Thompson, Mara L. Becker, Ryan S. Funk
Identification of disease and therapeutic biomarkers remains a significant challenge in the early diagnosis and effective treatment of juvenile idiopathic arthritis (JIA). In this study, plasma metabolomic profiling was conducted to identify disease-related metabolic biomarkers associated with JIA. Plasma samples from treatment-naïve JIA patients and non-JIA reference patients underwent global metabolomic profiling across discovery (60 JIA, 60 non-JIA) and replication (49 JIA, 38 non-JIA) cohorts. Univariate analysis identified significant metabolites (q-value ≤ 0.05), followed by enrichment analysis using ChemRICH and metabolic network mapping with MetaMapp and Cytoscape. Receiver operating characteristic (ROC) analysis determined the top discriminating biomarkers based on area under the curve (AUC) values. A total of over 800 metabolites were measured, consisting of 714 known and 155 unknown compounds. In the discovery cohort, 587 metabolites were significantly altered in JIA patients compared with the reference population (q < 0.05). In the replication cohort, 288 metabolites were significantly altered, with 78 overlapping metabolites demonstrating the same directional change in both cohorts. JIA was associated with a notable increase in plasma levels of sphingosine metabolites and fatty acid ethanolamides and decreased plasma levels of sarcosine, iminodiacetate, and the unknown metabolite X-12462. Chemical enrichment analysis identified cycloparaffins in the form of naproxen and its metabolites, unsaturated lysophospholipids, saturated phosphatidylcholines, sphingomyelins, ethanolamines, and saturated ceramides as the top discriminating biochemical clusters. ROC curve analysis identified 11 metabolites classified as highly discriminatory based on an AUC > 0.90, with the top discriminating metabolite being sphinganine-1-phosphate (AUC = 0.98). This study identifies specific metabolic changes in JIA, particularly within sphingosine metabolism, through both discovery and replication cohorts. Plasma metabolomic profiling shows promise in pinpointing JIA-specific biomarkers, differentiating them from those in healthy controls and Crohn’s disease, which may improve diagnosis and treatment.
{"title":"Identification of Plasma Metabolomic Biomarkers of Juvenile Idiopathic Arthritis","authors":"Amar Kumar, Joshua Tatarian, Valentina Shakhnovich, Rachel L. Chevalier, Marc Sudman, Daniel J. Lovell, Susan D. Thompson, Mara L. Becker, Ryan S. Funk","doi":"10.3390/metabo14090499","DOIUrl":"https://doi.org/10.3390/metabo14090499","url":null,"abstract":"Identification of disease and therapeutic biomarkers remains a significant challenge in the early diagnosis and effective treatment of juvenile idiopathic arthritis (JIA). In this study, plasma metabolomic profiling was conducted to identify disease-related metabolic biomarkers associated with JIA. Plasma samples from treatment-naïve JIA patients and non-JIA reference patients underwent global metabolomic profiling across discovery (60 JIA, 60 non-JIA) and replication (49 JIA, 38 non-JIA) cohorts. Univariate analysis identified significant metabolites (q-value ≤ 0.05), followed by enrichment analysis using ChemRICH and metabolic network mapping with MetaMapp and Cytoscape. Receiver operating characteristic (ROC) analysis determined the top discriminating biomarkers based on area under the curve (AUC) values. A total of over 800 metabolites were measured, consisting of 714 known and 155 unknown compounds. In the discovery cohort, 587 metabolites were significantly altered in JIA patients compared with the reference population (q < 0.05). In the replication cohort, 288 metabolites were significantly altered, with 78 overlapping metabolites demonstrating the same directional change in both cohorts. JIA was associated with a notable increase in plasma levels of sphingosine metabolites and fatty acid ethanolamides and decreased plasma levels of sarcosine, iminodiacetate, and the unknown metabolite X-12462. Chemical enrichment analysis identified cycloparaffins in the form of naproxen and its metabolites, unsaturated lysophospholipids, saturated phosphatidylcholines, sphingomyelins, ethanolamines, and saturated ceramides as the top discriminating biochemical clusters. ROC curve analysis identified 11 metabolites classified as highly discriminatory based on an AUC > 0.90, with the top discriminating metabolite being sphinganine-1-phosphate (AUC = 0.98). This study identifies specific metabolic changes in JIA, particularly within sphingosine metabolism, through both discovery and replication cohorts. Plasma metabolomic profiling shows promise in pinpointing JIA-specific biomarkers, differentiating them from those in healthy controls and Crohn’s disease, which may improve diagnosis and treatment.","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"694 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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