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      Avocado fruit maturation and ripening: dynamics of aliphatic acetogenins and lipidomic profiles from mesocarp, idioblasts and seed

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          Avocado fruit contains aliphatic acetogenins (oft-acetylated, odd-chain fatty alcohols) with promising bioactivities for both medical and food industries. However, we have scarce knowledge about their metabolism. The present work aimed to study changes in acetogenin profiles from mesocarp, lipid-containing idioblasts, and seeds from ‘Hass’ cultivar during fruit development, germination, and three harvesting years. An untargeted LC-MS based lipidomic analysis was also conducted to profile the lipidome of avocado fruit in each tissue.


          The targeted analysis showed that acetogenin profiles and contents remained unchanged in avocado mesocarp during maturation and postharvest ripening, germination, and different harvesting years. However, a shift in the acetogenin profile distribution, accompanied with a sharp increase in concentration, was observed in seed during early maturation. Untargeted lipidomics showed that this shift was accompanied with remodeling of glycerolipids: TAGs and DAGs decreased during fruit growing in seed. Remarkably, the majority of the lipidome in mature seed was composed by acetogenins; we suggest that this tissue is able to synthesize them independently from mesocarp. On the other hand, lipid-containing idioblasts accumulated almost the entire acetogenin pool measured in the whole mesocarp, while only having 4% of the total fatty acids. The lipidome of this cell type changed the most when the fruit was ripening after harvesting, TAGs decreased while odd-chain DAGs increased. Notably, idioblast lipidome was more diverse than that from mesocarp.


          Evidence shown here suggests that idioblasts are the main site of acetogenin biosynthesis in avocado mesocarp. This work unveiled the prevalence of aliphatic acetogenins in the avocado fruit lipidome and evidenced TAGs as initial donors of the acetogenin backbones in its biosynthesis. It also sets evidence for acetogenins being included in future works aimed at characterizing the avocado seed, as they are a main component of their lipidome.

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          The online version of this article (10.1186/s12870-017-1103-6) contains supplementary material, which is available to authorized users.

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          A Language and environment for statistical computing

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            LMSD: LIPID MAPS structure database

            The LIPID MAPS Structure Database (LMSD) is a relational database encompassing structures and annotations of biologically relevant lipids. Structures of lipids in the database come from four sources: (i) LIPID MAPS Consortium's core laboratories and partners; (ii) lipids identified by LIPID MAPS experiments; (iii) computationally generated structures for appropriate lipid classes; (iv) biologically relevant lipids manually curated from LIPID BANK, LIPIDAT and other public sources. All the lipid structures in LMSD are drawn in a consistent fashion. In addition to a classification-based retrieval of lipids, users can search LMSD using either text-based or structure-based search options. The text-based search implementation supports data retrieval by any combination of these data fields: LIPID MAPS ID, systematic or common name, mass, formula, category, main class, and subclass data fields. The structure-based search, in conjunction with optional data fields, provides the capability to perform a substructure search or exact match for the structure drawn by the user. Search results, in addition to structure and annotations, also include relevant links to external databases. The LMSD is publicly available at
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              LIPID MAPS online tools for lipid research

              The LIPID MAPS consortium has developed a number of online tools for performing tasks such as drawing lipid structures and predicting possible structures from mass spectrometry (MS) data. A simple online interface has been developed to enable an end-user to rapidly generate a variety of lipid chemical structures, along with corresponding systematic names and ontological information. The structure-drawing tools are available for six categories of lipids: (i) fatty acyls, (ii) glycerolipids, (iii) glycerophospholipids, (iv) cardiolipins, (v) sphingolipids and (vi) sterols. Within each category, the structure-drawing tools support the specification of various parameters such as chain lengths at a specific sn position, head groups, double bond positions and stereochemistry to generate a specific lipid structure. The structure-drawing tools have also been integrated with a second set of online tools which predict possible lipid structures from precursor-ion and product-ion MS experimental data. The MS prediction tools are available for three categories of lipids: (i) mono/di/triacylglycerols, (ii) glycerophospholipids and (iii) cardiolipins. The LIPID MAPS online tools are publicly available at www.lipidmaps.org/tools/.

                Author and article information

                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                29 September 2017
                29 September 2017
                : 17
                [1 ]ISNI 0000 0001 2203 4701, GRID grid.419886.a, Escuela de Ingeniería y Ciencias, Campus Monterrey, , Tecnologico de Monterrey, ; Monterrey, Nuevo Leon Mexico
                [2 ]ISNI 0000 0001 2203 4701, GRID grid.419886.a, Cátedra de Bioinformática, Escuela de Medicina, , Tecnologico de Monterrey, ; Monterrey, Nuevo Leon Mexico
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funded by: Fundacion FEMSA
                Award ID: Nutrigenomics Fund
                Funded by: FundRef http://dx.doi.org/10.13039/501100003141, Consejo Nacional de Ciencia y Tecnología;
                Award ID: 256801
                Award Recipient :
                Research Article
                Custom metadata
                © The Author(s) 2017


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