Metabolites最新文献

{"title":"Green Tea with Rhubarb Root Reduces Plasma Lipids While Preserving Gut Microbial Stability in a Healthy Human Cohort.","authors":"Amanda J Lloyd, M J Pilar Martinez-Martin, Alina Warren-Walker, Matthew D Hitchings, Odin M Moron-Garcia, Alison Watson, Bernardo Villarreal-Ramos, Laura Lyons, Thomas Wilson, Gordon Allison, Manfred Beckmann","doi":"10.3390/metabo15020139","DOIUrl":"10.3390/metabo15020139","url":null,"abstract":"<p><p><b>Background/Objectives</b>: Cardiovascular diseases remain a leading cause of mortality and morbidity, and dyslipidaemia is one of the major risk factors. The widespread use of herbs and medicinal plants in traditional medicine has garnered increasing recognition as a valuable resource for increasing wellness and reducing the onset of disease. Several epidemiologic and clinical studies have shown that altering blood lipid profiles and maintaining gut homeostasis may protect against cardiovascular diseases. <b>Methods</b>: A randomised, active-controlled parallel human clinical trial (n = 52) with three herbal tea infusions (green (<i>Camellia sinensis</i>) tea with rhubarb root, green tea with senna, and active control green tea) daily for 21 days in a free-living healthy adult cohort was conducted to assess the potential for health benefits in terms of plasma lipids and gut health. Paired plasma samples were analysed using Afinion lipid panels (total cholesterol, LDL (low-density lipoprotein) cholesterol, HDL (high-density lipoprotein) cholesterol, triglycerides, and non-HDL cholesterol) and paired stool samples were analysed using 16S rRNA amplicon sequencing to determine bacterial diversity within the gut microbiome. <b>Results</b>: Among participants providing fasting blood samples before and after the intervention (n = 47), consumption of herbal rhubarb root tea and green tea significantly lowered total cholesterol, LDL-cholesterol, and non-HDL cholesterol (<i>p</i> < 0.05) in plasma after 21 days of daily consumption when compared with concentrations before the intervention. No significant change was observed in the senna tea group. In participants providing stool samples (n = 48), no significant differences in overall microbial composition were observed between pre- and post-intervention, even at the genus level. While no significant changes in overall microbial composition were observed, specific bacterial genera, such as Dorea spp., showed correlations with LDL cholesterol concentrations, suggesting potential microbiota-mediated effects of tea consumption. Diet and BMI was maintained in each of the three groups before and after the trial. <b>Conclusions</b>: It was found that drinking a cup of rhubarb root herbal or green tea infusion for 21 days produced beneficial effects on lipid profiles and maintained gut eubiosis without observable adverse effects in a healthy human cohort. More studies are needed to fully understand the effects of rhubarb root and green tea in fatty acid metabolism and gut microbial composition.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857281/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492801","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}

{"title":"From Microbes to Metabolites: Advances in Gut Microbiome Research in Type 1 Diabetes.","authors":"Lente Blok, Nordin Hanssen, Max Nieuwdorp, Elena Rampanelli","doi":"10.3390/metabo15020138","DOIUrl":"10.3390/metabo15020138","url":null,"abstract":"<p><p><b>Background:</b> Type 1 diabetes (T1D) is a severe chronic T-cell mediated autoimmune disease that attacks the insulin-producing beta cells of the pancreas. The multifactorial nature of T1D involves both genetic and environmental components, with recent research focusing on the gut microbiome as a crucial environmental factor in T1D pathogenesis. The gut microbiome and its metabolites play an important role in modulating immunity and autoimmunity. In recent years, studies have revealed significant alterations in the taxonomic and functional composition of the gut microbiome associated with the development of islet autoimmunity and T1D. These changes include reduced production of short-chain fatty acids, altered bile acid and tryptophan metabolism, and increased intestinal permeability with consequent perturbations of host (auto)immune responses. <b>Methods/Results:</b> In this review, we summarize and discuss recent observational, mechanistic and etiological studies investigating the gut microbiome in T1D and elucidating the intricate role of gut microbes in T1D pathogenesis. Moreover, we highlight the recent advances in intervention studies targeting the microbiota for the prevention or treatment of human T1D. <b>Conclusions:</b> A deeper understanding of the evolution of the gut microbiome before and after T1D onset and of the microbial signals conditioning host immunity may provide us with essential insights for exploiting the microbiome as a prognostic and therapeutic tool.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857261/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492798","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}

{"title":"Matrix Linear Models for Connecting Metabolite Composition to Individual Characteristics.","authors":"Gregory Farage, Chenhao Zhao, Hyo Young Choi, Timothy J Garrett, Marshall B Elam, Katerina Kechris, Śaunak Sen","doi":"10.3390/metabo15020140","DOIUrl":"10.3390/metabo15020140","url":null,"abstract":"<p><p><i><b>Background/Objectives:</b></i> High-throughput metabolomics data provide a detailed molecular window into biological processes. We consider the problem of assessing how association of metabolite levels with individual (sample) characteristics, such as sex or treatment, depend on metabolite characteristics such as pathways. Typically, this is done using a two-step process. In the first step, we assess the association of each metabolite with individual characteristics. In the second step, an enrichment analysis is performed by metabolite characteristics. <i><b>Methods:</b></i> We combine the two steps using a bilinear model based on the matrix linear model (MLM) framework previously developed for high-throughput genetic screens. Our method can estimate relationships in metabolites sharing known characteristics, whether categorical (such as type of lipid or pathway) or numerical (such as number of double bonds in triglycerides). <i><b>Results:</b></i> We demonstrate the flexibility and interoperability of MLMs by applying them to three metabolomic studies. We show that our approach can separate the contribution of the overlapping triglyceride characteristics, such as the number of double bonds and the number of carbon atoms. <i><b>Conclusion:</b></i> The matrix linear model offers a flexible, efficient, and interpretable framework for integrating external information and examining complex relationships in metabolomics data. Our method has been implemented in the open-source Julia package, MatrixLM. Data analysis scripts with example data analyses are also available.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857268/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492831","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}

{"title":"<i>Broussonetia papyrifera</i> Pollen Metabolome Insights, Allergenicity, and Dispersal in Response to Climate Change Variables.","authors":"Muhammad Humayun, Saadia Naseem, Richard E Goodman, Zahid Ali","doi":"10.3390/metabo15020137","DOIUrl":"10.3390/metabo15020137","url":null,"abstract":"<p><p><b>Background/Objectives</b>: <i>Broussonetia papyrifera</i> is a tree-producing allergenic pollen that grows in varied climatic conditions worldwide and causes pollen allergies in susceptible humans. This study aimed to investigate <i>B. papyrifera</i> pollen morphology, pollen metabolome, pollen allergenicity, and climate change's impact on the plant habitat suitability in the future. <b>Methods</b>: Tree pollen was collected in spring from different regions of Pakistan. Pollen samples were subjected to morphological analysis, Fourier transform infrared spectroscopy (FTIR), liquid chromatography-mass spectrometry (LC-MS/MS), and immunoblotting. <b>Results</b>: MaxEnt modeling predicted the tree's future-growth invasion into new regions. Scanning electron microscopy (SEM) and FTIR displayed regional differences in pollen morphology and metabolome correlated to shifts in climatic variables. LC-MS/MS analysis detected four lipids that can potentially stimulate inflammatory responses. Pollen protein immunoblotting studies identified a putative 15 kDa novel allergen and verified previously known 40 kDa, 33 kDa, and 10 kDa allergens. <i>B. papyrifera</i> MaxEnt modeling through ACCESS1.0 and CCSM4 under 2-greenhouse gas emissions scenarios {representative concentration pathway (RCP) 4.5 and 8.5} projected the tree invasion by the years 2050 and 2070. <b>Conclusions</b>: The study findings demonstrate that differences in climatic variables affect <i>B. papyrifera</i>-pollen metabolome and predict the habitat suitability of the tree for invasion in the future. The study results provide a model system for studying other species' pollen morphology, metabolome, future habitat suitability for plant invasion, and associated allergies in response to climate change.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857163/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492724","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}

{"title":"The Adaptation of MCF-7 Breast Cancer Spheroids to the Chemotherapeutic Doxorubicin: The Dynamic Role of Phase I Drug Metabolizing Enzymes.","authors":"Daniel Crispim, Carolina Ramos, Francisco Esteves, Michel Kranendonk","doi":"10.3390/metabo15020136","DOIUrl":"10.3390/metabo15020136","url":null,"abstract":"<p><p><b>Background/Objectives:</b> Drug resistance (DR) is a major challenge in cancer therapy, contributing to approximately 90% of cancer-related deaths. While alterations in drug metabolism are known to be key drivers of DR, their role-particularly in the early stages of acquired chemoresistance-remains understudied. Phase I drug-metabolizing enzymes (DMEs), especially cytochrome P450s (CYPs), significantly influence the metabolic fate of chemotherapeutic agents, directly affecting drug response. This study aimed to investigate the role of Phase I DMEs in the early metabolic adaptation of breast cancer (BC) MCF-7 cells to doxorubicin (DOX). <b>Methods:</b> Four types of spheroids were generated from MCF-7 cells that were either DOX-sensitive (DOX^S) or adapted to low concentrations of the chemotherapeutic agent (DOX^A 25, 35, and 45 nM). The expression levels of 92 Phase I DMEs and the activities of specific CYP isoforms were assessed in both DOX^S and DOX^A spheroids. <b>Results:</b> A total of twenty-four DMEs, including fifteen CYPs and nine oxidoreductases, were found to be differentially expressed in DOX^A spheroids. Pathway analysis identified key roles for the differentially expressed DMEs in physiologically relevant pathways, including the metabolism of drugs, arachidonic acid, retinoic acid, and vitamin D. <b>Conclusions:</b> The deconvolution of these pathways highlights a highly dynamic process driving early-stage DOX resistance, with a prominent role of CYP3A-dependent metabolism in DOX adaptation. Our findings provide valuable insights into the underlying molecular mechanisms driving the early adaptation of MCF-7 cells to DOX exposure.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857127/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492804","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}

{"title":"Integrated Analyses of the Mechanism of Flower Color Formation in Alfalfa (<i>Medicago sativa</i>).","authors":"Zhaozhu Wen, Huancheng Liu, Qian Zhang, Xuran Lu, Kai Jiang, Qinyan Bao, Zhifei Zhang, Guofeng Yang, Zeng-Yu Wang","doi":"10.3390/metabo15020135","DOIUrl":"10.3390/metabo15020135","url":null,"abstract":"<p><strong>Background: </strong>Alfalfa (<i>Medicago sativa</i>) is one of the most valuable forages in the world. As an outcrossing species, it needs bright flowers to attract pollinators to deal with self-incompatibility. Although various flower colors have been observed and described in alfalfa a long time ago, the biochemical and molecular mechanism of its color formation is still unclear.</p><p><strong>Methods: </strong>By analyzing alfalfa lines with five contrasting flower colors including white (cream-colored), yellow, lavender (purple), dark purple and dark blue, various kinds and levels of anthocyanins, carotenoids and other flavonoids were detected in different colored petals, and their roles in color formation were revealed.</p><p><strong>Results: </strong>Notably, the content of delphinidin-3,5-<i>O</i>-diglucoside in lines 3, 4 and 5 was 58.88, 100.80 and 94.07 times that of line 1, respectively. Delphinidin-3,5-<i>O</i>-diglucoside was the key factor for purple and blue color formation. Lutein and β-carotene were the main factors for the yellow color formation. By analyzing differentially expressed genes responsible for specific biochemical pathways and compounds, 27 genes were found to be associated with purple and blue color formation, and 14 genes were found to play an important role in yellow color formation.</p><p><strong>Conclusions: </strong>The difference in petal color between white, purple and blue petals was mainly caused by the accumulation of delphinidin-3,5-O-diglucoside. The difference in petal color between white and yellow petals was mainly affected by the production of lutein and β-carotene. These findings provide a basis for understanding the biochemical and molecular mechanism of alfalfa flower color formation.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857827/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492819","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}

{"title":"Metabolomic Insights into Attention Deficit Hyperactivity Disorder: A Scoping Review.","authors":"Maria Jose Muñoz-Zabaleta, Nicolás Garzón Rodríguez, Luis Eduardo Díaz-Barrera, Maria Fernanda Quiroz-Padilla","doi":"10.3390/metabo15020133","DOIUrl":"10.3390/metabo15020133","url":null,"abstract":"<p><p><b>Background /Objectives</b> Attention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental condition, and symptoms persist into adulthood. Its etiology, though recognized as multifactorial, is still under discussion. Metabolomics helps us to identify pathways associated with functional and structural changes that may be related to symptomatology. This study aimed to characterize potentially altered metabolic pathways and associated biochemical reactions in ADHD. <b>Methods:</b> A scoping review of experimental research was conducted using PubMed, Web of Science, and Scopus using PRISMA ScR. Fifty-five studies were eligible for data extraction, of which fifteen met the criteria for inclusion in the review. Subsequently, the identified metabolites were analyzed in the context of the literature to recognize possible discordant pathways in the disorder. <b>Results:</b> Two groups of relevant neuromodulators of ADHD were found: precursors of monoamines and polyunsaturated fatty acids. The literature was reviewed to discover potential implicated pathways and new metabolites of interest. <b>Conclusions:</b> The study of ADHD biomarkers should focus on measuring precursor, intermediate, and final metabolites of polyunsaturated fatty acids and monoamines in panels or through untargeted analysis to improve the understanding of the pathology and individualization of treatments.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857725/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492449","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}

{"title":"Metabolomic Profiling of the Striatum in <i>Shank3</i> Knockout ASD Rats: Effects of Early Swimming Regulation.","authors":"Yunchen Meng, Yiling Hu, Yaqi Xue, Zhiping Zhen","doi":"10.3390/metabo15020134","DOIUrl":"10.3390/metabo15020134","url":null,"abstract":"<p><p><b>Objectives:</b> This study aimed to investigate the regulatory impact of early swimming intervention on striatal metabolism in <i>Shank3</i> gene knockout ASD model rats. <b>Methods:</b><i>Shank3</i> gene knockout exon 11-21 male 8-day-old SD rats were used as experimental subjects and randomly divided into the following three groups: a <i>Shank3</i> knockout control group (KC), a wild-type control group (WC) from the same litter, and a <i>Shank3</i> knockout swimming group (KS). The rats in the exercise group received early swimming intervention for 8 weeks starting at 8 days old. LC-MS metabolism was employed to detect the changes in metabolites in the striatum. <b>Results:</b> There were 17 differential metabolites (14 down-regulated) between the KC and WC groups, 19 differential metabolites (18 up-regulated) between the KS and KC groups, and 22 differential metabolites (18 up-regulated) between the KS and WC groups. <b>Conclusions:</b> The metabolism of striatum in <i>Shank3</i> knockout ASD model rats is disrupted, involving metabolites related to synaptic morphology, and the Glu and GABAergic synapses are abnormal. Early swimming intervention regulated the striatal metabolome group of the ASD model rats, with differential metabolites primarily related to nerve development, synaptic membrane structure, and synaptic signal transduction.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857520/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492483","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}

{"title":"Meta-Analysis of Abiotic Conditions Affecting Exopolysaccharide Production in Cyanobacteria.","authors":"Shijie Wu, Fuwen Wang, Hong Wang, Cong Shen, Kaiqiang Yu","doi":"10.3390/metabo15020131","DOIUrl":"10.3390/metabo15020131","url":null,"abstract":"<p><p><b>Background</b>: cyanobacterial exopolysaccharides (EPSs) exhibit diverse biological and physicochemical properties, making them valuable for applications in environmental remediation, soil improvement, wastewater treatment, and bioenergy production. <b>Results</b>: the production of cyanobacterial EPSs is significantly influenced by various factors, including abiotic factors and strains. Recent research has focused on optimizing EPS production by regulating key abiotic factors such as light, temperature, pH, and nutritional conditions. This review systematically compiles and analyzes published data on the effects of abiotic factors on cyanobacterial EPS biosynthesis, with a focus on genus-specific responses. Using meta-analysis techniques, we provide a comprehensive overview of the key factors influencing EPS production. Light and nutrient conditions are the most significant factors affecting EPS production, with high light intensities and optimal nutrient conditions enhancing EPS synthesis. Optimal temperature ranges and pH levels are essential for maximizing EPS production, and cyanobacteria exhibit genus-specific responses to variations in these factors. The addition of specific nutrients, such as NaCl, trace metals (e.g., Mg, Zn, Cu), and elevated CO₂ levels, significantly impacts EPS production. <b>Conclusions</b>: the response to these factors varies among different cyanobacterial genera, highlighting the need for genus-specific optimization strategies. This review provides a theoretical basis for optimizing EPS production across diverse cyanobacterial genera and for understanding multi-factor interactions and practical applications in future research.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857606/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492833","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}

{"title":"Deep Learning-Based Molecular Fingerprint Prediction for Metabolite Annotation.","authors":"Hoi Yan Katharine Chau, Xinran Zhang, Habtom W Ressom","doi":"10.3390/metabo15020132","DOIUrl":"10.3390/metabo15020132","url":null,"abstract":"<p><p><b>Background/Objectives:</b> Liquid chromatography coupled with mass spectrometry (LC-MS) is a commonly used platform for many metabolomics studies. However, metabolite annotation has been a major bottleneck in these studies in part due to the limited publicly available spectral libraries, which consist of tandem mass spectrometry (MS/MS) data acquired from just a fraction of known compounds. Application of deep learning methods is increasingly reported as an alternative to spectral matching due to their ability to map complex relationships between molecular fingerprints and mass spectrometric measurements. The objectives of this study are to investigate deep learning methods for molecular fingerprint based on MS/MS spectra and to rank putative metabolite IDs according to similarity of their known and predicted molecular fingerprints. <b>Methods</b>: We trained three types of deep learning methods to model the relationships between molecular fingerprints and MS/MS spectra. Prior to training, various data processing steps, including scaling, binning, and filtering, were performed on MS/MS spectra obtained from National Institute of Standards and Technology (NIST), MassBank of North America (MoNA), and Human Metabolome Database (HMDB). Furthermore, selection of the most relevant <i>m</i>/<i>z</i> bins and molecular fingerprints was conducted. The trained deep learning models were evaluated on ranking putative metabolite IDs obtained from a compound database for the challenges in Critical Assessment of Small Molecule Identification (CASMI) 2016, CASMI 2017, and CASMI 2022 benchmark datasets. <b>Results</b>: Feature selection methods effectively reduced redundant molecular and spectral features prior to model training. Deep learning methods trained with the truncated features have shown comparable performances against CSI:FingerID on ranking putative metabolite IDs. <b>Conclusion</b>: The results demonstrate a promising potential of deep learning methods for metabolite annotation.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 2","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857613/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143492742","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}