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Untargeted metabolomics approach using UPLC-ESI-QTOF-MS to explore the metabolome of fresh-cut iceberg lettuce

ABSTRACT: An untargeted metabolomics approach using UPLC-ESI-QTOF-MS was performed to explore the metabolome of iceberg lettuce and the changes related to storage time and genetics. Two cultivars with different browning susceptibility, fast- browning (FB) and slow-browning (SB) were studied juts after cutting (d0) and after 5 days of storage (d5). Extraction, metabolic profiling, and data-pretreatment procedures were optimized to obtain a robust and reliable data set. Preliminary principal component analysis (PCA) and hierarchical cluster analysis (HCA) of the full dataset (around 8551 extracted, aligned and filtered metabolites) showed a clear separation between the different samples (FB-d0, FB-d5, SB-d0, and SB-d5), highlighting a clear storage time-dependent effect. After statistical analysis applying Student´s t-test, 536 metabolites were detected as significantly different between d0 and d5 of storage in FB and 633 in SB. Some metabolites (221) were common to both cultivars. Out of these significant compounds, 22 were tentatively identified by matching their molecular formulae with those previously reported in the literature. Five families of metabolites were identified, some of them closely related to quality loss: amino acids, phenolic compounds, sesquiterpene lactones, fatty acids, and lysophospholipids. All compounds showed a clear trend to decrease at d5 except phenolic compounds that increased after storage. Overall, cutting and storage were shown to have a significant impact on the changes of lettuce metabolomics, with different trends depending on the browning susceptibility.

INSTRUMENT(S): 6540 Q-TOF LC/MS (Agilent)

SUBMITTER: Francisco Tomas-Barberan

PROVIDER: MTBLS343 | MetaboLights | 2017-08-03

REPOSITORIES: MetaboLights

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Untargeted metabolomics approach using UPLC-ESI-QTOF-MS to explore the metabolome of fresh-cut iceberg lettuce

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