The Human Metabolome Database or HMDB (https://hmdb.ca) has been providing comprehensive reference information about human metabolites and their associated biological, physiological and chemical properties since 2007. Over the past 15 years, the HMDB has grown and evolved significantly to meet the needs of the metabolomics community and respond to continuing changes in internet and computing technology. This year's update, HMDB 5.0, brings a number of important improvements and upgrades to the database. These should make the HMDB more useful and more appealing to a larger cross-section of users. In particular, these improvements include: (i) a significant increase in the number of metabolite entries (from 114 100 to 217 920 compounds); (ii) enhancements to the quality and depth of metabolite descriptions; (iii) the addition of new structure, spectral and pathway visualization tools; (iv) the inclusion of many new and much more accurately predicted spectral data sets, including predicted NMR spectra, more accurately predicted MS spectra, predicted retention indices and predicted collision cross section data and (v) enhancements to the HMDB’s search functions to facilitate better compound identification. Many other minor improvements and updates to the content, the interface, and general performance of the HMDB website have also been made. Overall, we believe these upgrades and updates should greatly enhance the HMDB’s ease of use and its potential applications not only in human metabolomics but also in exposomics, lipidomics, nutritional science, biochemistry and clinical chemistry.
The Natural Products Magnetic Resonance Database (NP-MRD) is a comprehensive, freely available electronic resource for the deposition, distribution, searching and retrieval of nuclear magnetic resonance (NMR) data on natural products, metabolites and other biologically derived chemicals. NMR spectroscopy has long been viewed as the ‘gold standard’ for the structure determination of novel natural products and novel metabolites. NMR is also widely used in natural product dereplication and the characterization of biofluid mixtures (metabolomics). All of these NMR applications require large collections of high quality, well-annotated, referential NMR spectra of pure compounds. Unfortunately, referential NMR spectral collections for natural products are quite limited. It is because of the critical need for dedicated, open access natural product NMR resources that the NP-MRD was funded by the National Institute of Health (NIH). Since its launch in 2020, the NP-MRD has grown quickly to become the world's largest repository for NMR data on natural products and other biological substances. It currently contains both structural and NMR data for nearly 41,000 natural product compounds from >7400 different living species. All structural, spectroscopic and descriptive data in the NP-MRD is interactively viewable, searchable and fully downloadable in multiple formats. Extensive hyperlinks to other databases of relevance are also provided. The NP-MRD also supports community deposition of NMR assignments and NMR spectra (1D and 2D) of natural products and related meta-data. The deposition system performs extensive data enrichment, automated data format conversion and spectral/assignment evaluation. Details of these database features, how they are implemented and plans for future upgrades are also provided. The NP-MRD is available at https://np-mrd.org.
Introduction Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS) mutations occur in approximately one-third of colorectal (CRC) tumours and have been associated with poor prognosis and resistance to some therapeutics. In addition to the well-documented pro-tumorigenic role of mutant Ras alleles, there is some evidence suggesting that not all KRAS mutations are equal and the position and type of amino acid substitutions regulate biochemical activity and transforming capacity of KRAS mutations. Objectives To investigate the metabolic signatures associated with different KRAS mutations in codons 12, 13, 61 and 146 and to determine what metabolic pathways are affected by different KRAS mutations. Methods We applied an NMR-based metabonomics approach to compare the metabolic profiles of the intracellular extracts and the extracellular media from isogenic human SW48 CRC cell lines with different KRAS mutations in codons 12 (G12D, G12A, G12C, G12S, G12R, G12V), 13 (G13D), 61 (Q61H) and 146 (A146T) with their wild-type counterpart. We used false discovery rate (FDR)-corrected analysis of variance (ANOVA) to determine metabolites that were statistically significantly different in concentration between the different mutants. Results CRC cells carrying distinct KRAS mutations exhibited differential metabolic remodelling, including differences in glycolysis, glutamine utilization and in amino acid, nucleotide and hexosamine metabolism. Conclusions Metabolic differences among different KRAS mutations might play a role in their different responses to anticancer treatments and hence could be exploited as novel metabolic vulnerabilities to develop more effective therapies against oncogenic KRAS.
It was recently demonstrated in mice that knockout of the flavin-containing monooxygenase 5 gene, Fmo5, slows metabolic ageing via pleiotropic effects. We have now used an NMR-based metabonomics approach to study the effects of ageing directly on the metabolic profiles of urine and plasma from male, wild-type C57BL/6J and Fmo5−/− (FMO5 KO) mice back-crossed onto the C57BL/6J background. The aim of this study was to identify metabolic signatures that are associated with ageing in both these mouse lines and to characterize the age-related differences in the metabolite profiles between the FMO5 KO mice and their wild-type counterparts at equivalent time points. We identified a range of age-related biomarkers in both urine and plasma. Some metabolites, including urinary 6-hydroxy-6-methylheptan-3-one (6H6MH3O), a mouse sex pheromone, showed similar patterns of changes with age, regardless of genetic background. Others, however, were altered only in the FMO5 KO, or only in the wild-type mice, indicating the impact of genetic modifications on mouse ageing. Elevated concentrations of urinary taurine represent a distinctive, ageing-related change observed only in wild-type mice.
Individual variability in drug response is a key challenge in current clinical practice and in drug discovery and development. Pharmacological response is closely associated with drug concentration at the site of action and therefore knowledge of drug pharmacokinetics is vital to delivering effective therapy. In addition to genetic polymorphisms, environmental factors also play an important role in determining drug efficacy, safety, metabolism and pharmacokinetics. The newly emerging field of pharmacometabonomics uses information from pre-dose metabolite profiles to predict individual drug responses, can be sensitive to both genetic and environmental factors and thus has great promise to help the future delivery of personalized medicine. This article introduces pharmacometabonomics and covers its application to the prediction of pharmacokinetics. EditorialPersonalised or stratified therapy is a key goal for 21 st century medicine in order to maximize therapeutic efficacy and minimize the likelihood of adverse drug reactions for groups of patients. In addition, personalised medicine has the potential to substantially enhance the process of drug discovery and development.[1] Thus far, personalized medicine has been mainly based on pharmacogenomics (PG), where an individual's genetic profile is used to
We previously showed that Fmo5−/− mice exhibit a lean phenotype and slower metabolic ageing. Their characteristics include lower plasma glucose and cholesterol, greater glucose tolerance and insulin sensitivity, and a reduction in age-related weight gain and whole-body fat deposition. In this paper, nuclear magnetic resonance (NMR) spectroscopy-based metabolite analyses of the urine of Fmo5−/− and wild-type mice identified two isomers of 2,3-butanediol as discriminating urinary biomarkers of Fmo5−/− mice. Antibiotic-treatment of Fmo5−/− mice increased plasma cholesterol concentration and substantially reduced urinary excretion of 2,3-butanediol isomers, indicating that the gut microbiome contributed to the lower plasma cholesterol of Fmo5−/− mice, and that 2,3-butanediol is microbially derived. Short- and long-term treatment of wild-type mice with a 2,3-butanediol isomer mix decreased plasma cholesterol and epididymal fat deposition but had no effect on plasma concentrations of glucose or insulin, or on body weight. In the case of long-term treatment, the effects were maintained after withdrawal of 2,3-butanediol. Short-, but not long-term treatment, also decreased plasma concentrations of triglycerides and non-esterified fatty acids. Fecal transplant from Fmo5−/− to wild-type mice had no effect on plasma cholesterol, and 2,3-butanediol was not detected in the urine of recipient mice, suggesting that the microbiota of the large intestine was not the source of 2,3-butanediol. However, 2,3-butanediol was detected in the stomach of Fmo5−/− mice, which was enriched for Lactobacillus genera, known to produce 2,3-butanediol. Our results indicate a microbial contribution to the phenotypic characteristic of Fmo5−/− mice of decreased plasma cholesterol and identify 2,3-butanediol as a potential agent for lowering plasma cholesterol.
Introduction KRAS was one of the earliest human oncogenes to be described and is one of the most commonly mutated genes in different human cancers, including colorectal cancer. Despite KRAS mutants being known driver mutations, KRAS has proved difficult to target therapeutically, necessitating a comprehensive understanding of the molecular mechanisms underlying KRAS-driven cellular transformation. Objectives To investigate the metabolic signatures associated with single copy mutant KRAS in isogenic human colorectal cancer cells and to determine what metabolic pathways are affected. Methods Using NMR-based metabonomics, we compared wildtype (WT)-KRAS and mutant KRAS effects on cancer cell metabolism using metabolic profiling of the parental KRASG13D/+ HCT116 cell line and its isogenic, derivative cell lines KRAS+/– and KRASG13D/–. Results Mutation in the KRAS oncogene leads to a general metabolic remodelling to sustain growth and counter stress, including alterations in the metabolism of amino acids and enhanced glutathione biosynthesis. Additionally, we show that KRASG13D/+ and KRASG13D/− cells have a distinct metabolic profile characterized by dysregulation of TCA cycle, up-regulation of glycolysis and glutathione metabolism pathway as well as increased glutamine uptake and acetate utilization. Conclusions Our study showed the effect of a single point mutation in one KRAS allele and KRAS allele loss in an isogenic genetic background, hence avoiding confounding genetic factors. Metabolic differences among different KRAS mutations might play a role in their different responses to anticancer treatments and hence could be exploited as novel metabolic vulnerabilities to develop more effective therapies against oncogenic KRAS. Graphical abstract
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