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      Production of Phloroglucinol, a Platform Chemical, in Arabidopsis using a Bacterial Gene

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          Abstract

          Phloroglucinol (1,3,5-trihydroxybenzene; PG) and its derivatives are phenolic compounds that are used for various industrial applications. Current methods to synthesize PG are not sustainable due to the requirement for carbon-based precursors and co-production of toxic byproducts. Here, we describe a more sustainable production of PG using plants expressing a native bacterial or a codon-optimized synthetic PhlD targeted to either the cytosol or chloroplasts. Transgenic lines were analyzed for the production of PG using gas and liquid chromatography coupled to mass spectroscopy. Phloroglucinol was produced in all transgenic lines and the line with the highest PhlD transcript level showed the most accumulation of PG. Over 80% of the produced PG was glycosylated to phlorin. Arabidopsis leaves have the machinery to glycosylate PG to form phlorin, which can be hydrolyzed enzymatically to produce PG. Furthermore, the metabolic profile of plants with PhlD in either the cytosol or chloroplasts was altered. Our results provide evidence that plants can be engineered to produce PG using a bacterial gene. Phytoproduction of PG using a bacterial gene paves the way for further genetic manipulations to enhance the level of PG with implications for the commercial production of this important platform chemical in plants.

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          Ca(2+)/calmodulin regulates salicylic-acid-mediated plant immunity.

          Intracellular calcium transients during plant-pathogen interactions are necessary early events leading to local and systemic acquired resistance. Salicylic acid, a critical messenger, is also required for both of these responses, but whether and how salicylic acid level is regulated by Ca(2+) signalling during plant-pathogen interaction is unclear. Here we report a mechanism connecting Ca(2+) signal to salicylic-acid-mediated immune response through calmodulin, AtSR1 (also known as CAMTA3), a Ca(2+)/calmodulin-binding transcription factor, and EDS1, an established regulator of salicylic acid level. Constitutive disease resistance and elevated levels of salicylic acid in loss-of-function alleles of Arabidopsis AtSR1 suggest that AtSR1 is a negative regulator of plant immunity. This was confirmed by epistasis analysis with mutants of compromised salicylic acid accumulation and disease resistance. We show that AtSR1 interacts with the promoter of EDS1 and represses its expression. Furthermore, Ca(2+)/calmodulin-binding to AtSR1 is required for suppression of plant defence, indicating a direct role for Ca(2+)/calmodulin in regulating the function of AtSR1. These results reveal a previously unknown regulatory mechanism linking Ca(2+) signalling to salicylic acid level.
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            Glycosylation Is a Major Regulator of Phenylpropanoid Availability and Biological Activity in Plants

            The phenylpropanoid pathway in plants is responsible for the biosynthesis of a huge amount of secondary metabolites derived from phenylalanine and tyrosine. Both flavonoids and lignins are synthesized at the end of this very diverse metabolic pathway, as well as many intermediate molecules whose precise biological functions remain largely unknown. The diversity of these molecules can be further increased under the action of UDP-glycosyltransferases (UGTs) leading to the production of glycosylated hydroxycinnamates and related aldehydes, alcohols and esters. Glycosylation can change phenylpropanoid solubility, stability and toxic potential, as well as influencing compartmentalization and biological activity. (De)-glycosylation therefore represents an extremely important regulation point in phenylpropanoid homeostasis. In this article we review recent knowledge on the enzymes involved in regulating phenylpropanoid glycosylation status and availability in different subcellular compartments. We also examine the potential link between monolignol glycosylation and lignification by exploring co-expression of lignin biosynthesis genes and phenolic (de)glycosylation genes. Of the different biological roles linked with their particular chemical properties, phenylpropanoids are often correlated with the plant's stress management strategies that are also regulated by glycosylation. UGTs can for instance influence the resistance of plants during infection by microorganisms and be involved in the mechanisms related to environmental changes. The impact of flavonoid glycosylation on the color of flowers, leaves, seeds and fruits will also be discussed. Altogether this paper underlies the fact that glycosylation and deglycosylation are powerful mechanisms allowing plants to regulate phenylpropanoid localisation, availability and biological activity.
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              RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data.

              Metabolomic data are frequently acquired using chromatographically coupled mass spectrometry (MS) platforms. For such datasets, the first step in data analysis relies on feature detection, where a feature is defined by a mass and retention time. While a feature typically is derived from a single compound, a spectrum of mass signals is more a more-accurate representation of the mass spectrometric signal for a given metabolite. Here, we report a novel feature grouping method that operates in an unsupervised manner to group signals from MS data into spectra without relying on predictability of the in-source phenomenon. We additionally address a fundamental bottleneck in metabolomics, annotation of MS level signals, by incorporating indiscriminant MS/MS (idMS/MS) data implicitly: feature detection is performed on both MS and idMS/MS data, and feature-feature relationships are determined simultaneously from the MS and idMS/MS data. This approach facilitates identification of metabolites using in-source MS and/or idMS/MS spectra from a single experiment, reduces quantitative analytical variation compared to single-feature measures, and decreases false positive annotations of unpredictable phenomenon as novel compounds. This tool is released as a freely available R package, called RAMClustR, and is sufficiently versatile to group features from any chromatographic-spectrometric platform or feature-finding software.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                07 December 2016
                2016
                : 6
                : 38483
                Affiliations
                [1 ]Department of Biology, Program in Molecular Plant Biology, Program in Cell and Molecular Biology, Colorado State University , Fort Collins, CO 80523, USA
                [2 ]Department of Botany, Faculty of Science, Zagazig University , Zagazig, 44519, Egypt
                [3 ]Proteomics and Metabolomics Facility, Colorado State University , Fort Collins, CO 80523, USA
                Author notes
                Article
                srep38483
                10.1038/srep38483
                5141504
                27924918
                531ccdfc-3676-404c-8424-4be88b674697
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International 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/4.0/

                History
                : 22 August 2016
                : 10 November 2016
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