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    Morphological and metabolic profiling of a tropical-adapted potato association panel subjected to water recovery treatment reveals new insights into plant vigor
    (Blackwell Publishing Ltd, 2020-09-01)
    Potato (Solanum tuberosum L.) is one of the world's most important crops, but it is facing major challenges due to climatic changes. To investigate the effects of intermittent drought on the natural variability of plant morphology and tuber metabolism in a novel potato association panel comprising 258 varieties we performed an augmented block design field study under normal irrigation and under water-deficit and recovery conditions in Ica, Peru. All potato genotypes were profiled for 45 morphological traits and 42 central metabolites via nuclear magnetic resonance. Statistical tests and norm of reaction analysis revealed that the observed variations were trait specific, that is, genotypic versus environmental. Principal component analysis showed a separation of samples as a result of conditional changes. To explore the relational ties between morphological traits and metabolites, correlation-based network analysis was employed, constructing one network for normal irrigation and one network for water-recovery samples. Community detection and difference network analysis highlighted the differences between the two networks, revealing a significant correlational link between fumarate and plant vigor. A genome-wide association study was performed for each metabolic trait. Eleven single nucleotide polymorphism (SNP) markers were associated with fumarate. Gene Ontology analysis of quantitative trait loci regions associated with fumarate revealed an enrichment of genes regulating metabolic processes. Three of the 11 SNPs were located within genes, coding for a protein of unknown function, a RING domain protein and a zinc finger protein ZAT2. Our findings have important implications for future potato breeding regimes, especially in countries suffering from climate change.
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    Pure shift nuclear magnetic resonance: a new tool for plant metabolomics
    (Journal of Visualized Experiments, 2021-01-01)
    Nuclear Magnetic Resonance (NMR) is one of the most powerful tools used in metabolomics. It stands as a highly accurate and reproducible method that not only provides quantitative data but also permits structural identification of the metabolites present in complex mixtures. Metabolic profiling by 1H NMR has proven useful in the study of various types of plant scenarios, which include the evaluation of crop conditions, harvest and post- harvest treatments, metabolic phenotyping, metabolic pathways, gene regulation, identification of biomarkers, chemotaxonomy, quality control, denomination of origin, among others. However, signal overlapping of the large number of resonances with expanded J-coupling multiplicities complicates the spectra analysis and its interpretation, and represents a limitation for classical 1H NMR profiling. In the last decade, novel NMR broadband homonuclear decoupling techniques through which multiplet signals collapse into single resonance lines - commonly called Pure Shift methods - have been developed to overcome the spectra resolution problem inherent to 1H NMR classical spectra. Here a step-by-step protocol of the plant extract preparation and the procedure to record optimal Pure Shift PSYCHE and SAPPHIRE-PSYCHE spectra in three different plant matrices - Vanilla plant leaves, potato tubers (S. tuberosum), and Cape gooseberries (P. peruviana) - is presented. The effect of the gain in resolution in metabolic identification, correlation analysis and multivariate analyses, as compared against classical spectra, is discussed.
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    Urine 1H-NMR metabolomics to discriminate neurocysticercosis patients from healthy controls: an exploratory study
    (American Society of Tropical Medicine and Hygiene, 2022-07-01)
    The diagnosis of neurocysticercosis (NCC) is principally based on neuroimaging (magnetic resonance imaging or computed tomography), instrumentation that is scarcely available in the rural regions where Taenia solium transmission, primarily occurs due to poor sanitation conditions. Immunological assays for antigen or antibody detection complement the neuroimaging approach. However, no field-applicable assays to diagnose viable NCC or to guide the referral of cases for neuroimaging or for appropriate management are available. We performed an exploratory study on urine and serum samples using 1H-nuclear magnetic resonance (NMR)-based metabolomics to discriminate NCC patients (n 5 14) from healthy control subjects (n 5 22). Metabolic profiles demonstrated a discrimination between the urines of NCC patients and noninfected control subjects with a moderate predictive accuracy (R2 5 0.999, Q2 5 0.434). NMR metabolomics analysis has been proven useful in depicting biomarkers linked to other infectious diseases, various types of cancer, and other disorders. Our results, albeit preliminary, open a door to the development of better methods for detecting NCC through the identification of biomarkers participating in disturbed metabolic pathways.
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