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      Metabolomics Analysis Reveals Tissue-Specific Metabolite Compositions in Leaf Blade and Traps of Carnivorous Nepenthes Plants

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          Abstract

          Nepenthes is a genus of carnivorous plants that evolved a pitfall trap, the pitcher, to catch and digest insect prey to obtain additional nutrients. Each pitcher is part of the whole leaf, together with a leaf blade. These two completely different parts of the same organ were studied separately in a non-targeted metabolomics approach in Nepenthes x ventrata, a robust natural hybrid. The first aim was the analysis and profiling of small (50–1000 m/ z) polar and non-polar molecules to find a characteristic metabolite pattern for the particular tissues. Second, the impact of insect feeding on the metabolome of the pitcher and leaf blade was studied. Using UPLC-ESI-qTOF and cheminformatics, about 2000 features (MS/MS events) were detected in the two tissues. They showed a huge chemical diversity, harboring classes of chemical substances that significantly discriminate these tissues. Among the common constituents of N. x ventrata are phenolics, flavonoids and naphthoquinones, namely plumbagin, a characteristic compound for carnivorous Nepenthales, and many yet-unknown compounds. Upon insect feeding, only in pitchers in the polar compounds fraction, small but significant differences could be detected. By further integrating information with cheminformatics approaches, we provide and discuss evidence that the metabolite composition of the tissues can point to their function.

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          Accurate profiling of lipidomes relies upon the quantitative and unbiased recovery of lipid species from analyzed cells, fluids, or tissues and is usually achieved by two-phase extraction with chloroform. We demonstrated that methyl-tert-butyl ether (MTBE) extraction allows faster and cleaner lipid recovery and is well suited for automated shotgun profiling. Because of MTBE's low density, lipid-containing organic phase forms the upper layer during phase separation, which simplifies its collection and minimizes dripping losses. Nonextractable matrix forms a dense pellet at the bottom of the extraction tube and is easily removed by centrifugation. Rigorous testing demonstrated that the MTBE protocol delivers similar or better recoveries of species of most all major lipid classes compared with the "gold-standard" Folch or Bligh and Dyer recipes.
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              Searching molecular structure databases with tandem mass spectra using CSI:FingerID.

              Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. We present a method for searching molecular structure databases using tandem MS data of small molecules. Our method computes a fragmentation tree that best explains the fragmentation spectrum of an unknown molecule. We use the fragmentation tree to predict the molecular structure fingerprint of the unknown compound using machine learning. This fingerprint is then used to search a molecular structure database such as PubChem. Our method is shown to improve on the competing methods for computational metabolite identification by a considerable margin.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                19 June 2020
                June 2020
                : 21
                : 12
                : 4376
                Affiliations
                [1 ]Research Group Plant Defense Physiology, Max Planck Institute for Chemical Ecology, 07745 Jena, Germany; adavila-lara@ 123456ice.mpg.de
                [2 ]Departamento de Biología, Universidad Nacional Autónoma de Nicaragua-León (UNAN), 21000 León, Nicaragua
                [3 ]Department of Natural Product Biosynthesis, Max Planck Institute for Chemical Ecology, 07745 Jena, Germany; clopez@ 123456ice.mpg.de (C.E.R.-L.); oconnor@ 123456ice.mpg.de (S.E.O.)
                Author notes
                [* ]Correspondence: amithoefer@ 123456ice.mpg.de
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-7595-8251
                https://orcid.org/0000-0001-9224-0455
                https://orcid.org/0000-0001-5229-6913
                Article
                ijms-21-04376
                10.3390/ijms21124376
                7352528
                32575527
                cdec2085-3068-4118-9dba-6f7b9f326987
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 18 May 2020
                : 17 June 2020
                Categories
                Article

                Molecular biology
                nepenthes,carnivorous plants,uplc-qtof-ms,metabolomics,tissue specificity,cheminformatics

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