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      The seco-iridoid pathway from Catharanthus roseus

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          Abstract

          The (seco)iridoids and their derivatives, the monoterpenoid indole alkaloids (MIAs), form two large families of plant-derived bioactive compounds with a wide spectrum of high-value pharmacological and insect-repellent activities. Vinblastine and vincristine, MIAs used as anticancer drugs, are produced by Catharanthus roseus in extremely low levels, leading to high market prices and poor availability. Their biotechnological production is hampered by the fragmentary knowledge of their biosynthesis. Here we report the discovery of the last four missing steps of the (seco)iridoid biosynthesis pathway. Expression of the eight genes encoding this pathway, together with two genes boosting precursor formation and two downstream alkaloid biosynthesis genes, in an alternative plant host, allows the heterologous production of the complex MIA strictosidine. This confirms the functionality of all enzymes of the pathway and highlights their utility for synthetic biology programmes towards a sustainable biotechnological production of valuable (seco)iridoids and alkaloids with pharmaceutical and agricultural applications.

          Abstract

          The (seco)iridoids and their monoterpenoid indole alkaloid (MIA) derivatives are plant-derived compounds with pharmaceutical applications. Here, the authors identify the last four missing steps of the (seco)iridoid pathway, which they reconstitute in an alternative plant host to produce the complex MIA, strictosidine.

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          Most cited references37

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          Cluster analysis and display of genome-wide expression patterns.

          A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
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            Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

            We present a statistical model to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST. Employing the expectation maximization algorithm, the analysis learns to distinguish correct from incorrect database search results, computing probabilities that peptide assignments to spectra are correct based upon database search scores and the number of tryptic termini of peptides. Using SEQUEST search results for spectra generated from a sample of known protein components, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides. This analysis makes it possible to filter large volumes of MS/MS database search results with predictable false identification error rates and can serve as a common standard by which the results of different research groups are compared.
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              A multicolored set of in vivo organelle markers for co-localization studies in Arabidopsis and other plants.

              Genome sequencing has resulted in the identification of a large number of uncharacterized genes with unknown functions. It is widely recognized that determination of the intracellular localization of the encoded proteins may aid in identifying their functions. To facilitate these localization experiments, we have generated a series of fluorescent organelle markers based on well-established targeting sequences that can be used for co-localization studies. In particular, this organelle marker set contains indicators for the endoplasmic reticulum, the Golgi apparatus, the tonoplast, peroxisomes, mitochondria, plastids and the plasma membrane. All markers were generated with four different fluorescent proteins (FP) (green, cyan, yellow or red FPs) in two different binary plasmids for kanamycin or glufosinate selection, respectively, to allow for flexible combinations. The labeled organelles displayed characteristic morphologies consistent with previous descriptions that could be used for their positive identification. Determination of the intracellular distribution of three previously uncharacterized proteins demonstrated the usefulness of the markers in testing predicted subcellular localizations. This organelle marker set should be a valuable resource for the plant community for such co-localization studies. In addition, the Arabidopsis organelle marker lines can also be employed in plant cell biology teaching labs to demonstrate the distribution and dynamics of these organelles.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                2041-1723
                07 April 2014
                : 5
                : 3606
                Affiliations
                [1 ]Sylvius Laboratory, Institute of Biology Leiden, Leiden University , Sylviusweg 72, PO Box 9505, Leiden 2300 RA, The Netherlands
                [2 ]Laboratory of Plant Physiology, Wageningen University, Droevendaalsesteeg 1 , Wageningen 6708 PB, The Netherlands
                [3 ]Institut de Biologie Moléculaire des Plantes, Unité Propre de Recherche 2357 du Centre National de la Recherche Scientifique, Université de Strasbourg , 28 rue Goethe, Strasbourg 67000, France
                [4 ]Institute of Plant Biology, University Zurich , Zollikerstrasse 107, Zurich CH-8008, Switzerland
                [5 ]CNRS; UMR 5546, Université de Toulouse; UPS; UMR 5546, Laboratoire de Recherche en Sciences Végétales , BP 42617 Auzeville, Castanet-Tolosan F-31326, France
                [6 ]Department of Plant Systems Biology, VIB and Department of Plant Biotechnology and Bioinformatics, Ghent University , Technologiepark 927, Gent B-9052, Belgium
                [7 ]Industrial Biotechnology, VTT Technical Research Centre of Finland , P.O. Box 1000, FI-02044 VTT (Espoo), Finland
                [8 ]These authors contributed equally to this work
                [9 ]Present address: Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, Neuchatel 2000, Switzerland
                [10 ]Present address: Plant Production Systems Group, Wageningen University, P.O. Box 430, Wageningen 6700 AK, The Netherlands
                Author notes
                Article
                ncomms4606
                10.1038/ncomms4606
                3992524
                24710322
                3d93b95e-9507-43be-9503-163d4cdddad4
                Copyright © 2014, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/

                History
                : 23 August 2013
                : 10 March 2014
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