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Metabolomics of Myrcia bella Populations in Brazilian Savanna Reveals Strong Influence of Environmental Factors on Its Specialized Metabolism
Metabolomics of Myrcia bella Populations in Brazilian Savanna Reveals Strong Influence of Environmental Factors on Its Specialized Metabolism
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Metabolomics of Myrcia bella Populations in Brazilian Savanna Reveals Strong Influence of Environmental Factors on Its Specialized Metabolism
Metabolomics of Myrcia bella Populations in Brazilian Savanna Reveals Strong Influence of Environmental Factors on Its Specialized Metabolism

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Metabolomics of Myrcia bella Populations in Brazilian Savanna Reveals Strong Influence of Environmental Factors on Its Specialized Metabolism
Metabolomics of Myrcia bella Populations in Brazilian Savanna Reveals Strong Influence of Environmental Factors on Its Specialized Metabolism
Journal Article

Metabolomics of Myrcia bella Populations in Brazilian Savanna Reveals Strong Influence of Environmental Factors on Its Specialized Metabolism

2020
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Overview
Environmental conditions influence specialized plant metabolism. However, many studies aiming to understand these modulations have been conducted with model plants and/or under controlled conditions, thus not reflecting the complex interaction between plants and environment. To fully grasp these interactions, we investigated the specialized metabolism and genetic diversity of a native plant in its natural environment. We chose Myrcia bella due to its medicinal interest and occurrence in Brazilian savanna regions with diverse climate and soil conditions. An LC-HRMS-based metabolomics approach was applied to analyze 271 samples harvested across seven regions during the dry and rainy season. Genetic diversity was assessed in a subset of 40 samples using amplified fragment length polymorphism. Meteorological factors including rainfall, temperature, radiation, humidity, and soil nutrient and mineral composition were recorded in each region and correlated with chemical variation through multivariate analysis (MVDA). Marker compounds were selected using a statistically informed molecular network and annotated by dereplication against an in silico database of natural products. The integrated results evidenced different chemotypes, with variation in flavonoid and tannin content mainly linked to soil conditions. Different levels of genetic diversity and distance of populations were found to be correlated with the identified chemotypes. These observations and the proposed analytical workflow contribute to the global understanding of the impact of abiotic factors and genotype on the accumulation of given metabolites and, therefore, could be valuable to guide further medicinal exploration of native species.