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      A sex-inducing pheromone triggers cell cycle arrest and mate attraction in the diatom Seminavis robusta

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          Abstract

          Although sexual reproduction is believed to play a major role in the high diversification rates and species richness of diatoms, a mechanistic understanding of diatom life cycle control is virtually lacking. Diatom sexual signalling is controlled by a complex, yet largely unknown, pheromone system. Here, a sex-inducing pheromone (SIP +) of the benthic pennate diatom Seminavis robusta was identified by comparative metabolomics, subsequently purified, and physicochemically characterized. Transcriptome analysis revealed that SIP + triggers the switch from mitosis-to-meiosis in the opposing mating type, coupled with the transcriptional induction of proline biosynthesis genes, and the release of the proline-derived attraction pheromone. The induction of cell cycle arrest by a pheromone, chemically distinct from the one used to attract the opposite mating type, highlights the existence of a sophisticated mechanism to increase chances of mate finding, while keeping the metabolic losses associated with the release of an attraction pheromone to a minimum.

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          Most cited references35

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          XCMS Online: a web-based platform to process untargeted metabolomic data.

          Recently, interest in untargeted metabolomics has become prevalent in the general scientific community among an increasing number of investigators. The majority of these investigators, however, do not have the bioinformatic expertise that has been required to process metabolomic data by using command-line driven software programs. Here we introduce a novel platform to process untargeted metabolomic data that uses an intuitive graphical interface and does not require installation or technical expertise. This platform, called XCMS Online, is a web-based version of the widely used XCMS software that allows users to easily upload and process liquid chromatography/mass spectrometry data with only a few mouse clicks. XCMS Online provides a solution for the complete untargeted metabolomic workflow including feature detection, retention time correction, alignment, annotation, statistical analysis, and data visualization. Results can be browsed online in an interactive, customizable table showing statistics, chromatograms, and putative METLIN identities for each metabolite. Additionally, all results and images can be downloaded as zip files for offline analysis and publication. XCMS Online is available at https://xcmsonline.scripps.edu.
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            Independent filtering increases detection power for high-throughput experiments.

            With high-dimensional data, variable-by-variable statistical testing is often used to select variables whose behavior differs across conditions. Such an approach requires adjustment for multiple testing, which can result in low statistical power. A two-stage approach that first filters variables by a criterion independent of the test statistic, and then only tests variables which pass the filter, can provide higher power. We show that use of some filter/test statistics pairs presented in the literature may, however, lead to loss of type I error control. We describe other pairs which avoid this problem. In an application to microarray data, we found that gene-by-gene filtering by overall variance followed by a t-test increased the number of discoveries by 50%. We also show that this particular statistic pair induces a lower bound on fold-change among the set of discoveries. Independent filtering-using filter/test pairs that are independent under the null hypothesis but correlated under the alternative-is a general approach that can substantially increase the efficiency of experiments.
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              Natriuretic peptides, their receptors, and cyclic guanosine monophosphate-dependent signaling functions.

              Natriuretic peptides are a family of structurally related but genetically distinct hormones/paracrine factors that regulate blood volume, blood pressure, ventricular hypertrophy, pulmonary hypertension, fat metabolism, and long bone growth. The mammalian members are atrial natriuretic peptide, B-type natriuretic peptide, C-type natriuretic peptide, and possibly osteocrin/musclin. Three single membrane-spanning natriuretic peptide receptors (NPRs) have been identified. Two, NPR-A/GC-A/NPR1 and NPR-B/GC-B/NPR2, are transmembrane guanylyl cyclases, enzymes that catalyze the synthesis of cGMP. One, NPR-C/NPR3, lacks intrinsic enzymatic activity and controls the local concentrations of natriuretic peptides through constitutive receptor-mediated internalization and degradation. Single allele-inactivating mutations in the promoter of human NPR-A are associated with hypertension and heart failure, whereas homozygous inactivating mutations in human NPR-B cause a form of short-limbed dwarfism known as acromesomelic dysplasia type Maroteaux. The physiological effects of natriuretic peptides are elicited through three classes of cGMP binding proteins: cGMP-dependent protein kinases, cGMP-regulated phosphodiesterases, and cyclic nucleotide-gated ion channels. In this comprehensive review, the structure, function, regulation, and biological consequences of natriuretic peptides and their associated signaling proteins are described.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                20 January 2016
                2016
                : 6
                : 19252
                Affiliations
                [1 ]Protistology and Aquatic Ecology, Department of Biology, Ghent University , 9000 Ghent, Belgium
                [2 ]Department of Plant Systems Biology , VIB, B–9052 Ghent, Belgium
                [3 ]Department of Plant Biotechnology and Bioinformatics, Ghent University , B–9052 Ghent, Belgium
                [4 ]Institute for Inorganic and Analytical Chemistry, Bioorganic Analytics, Friedrich Schiller University , 07743 Jena, Germany
                [5 ]Department of Biology, California State University , 9001 Stockdale Highway, Bakersfield, CA 93311, USA
                [6 ]Department of Applied Mathematics, Computer Science and Statistics, Ghent University , 9000 Ghent, Belgium
                [7 ]Department of Biology, Norwegian University of Science and Technology , 7491 Trondheim, Norway
                Author notes
                Article
                srep19252
                10.1038/srep19252
                4726125
                26786712
                c153dc7f-f8b4-41a2-8211-efdbc926d1ea
                Copyright © 2016, Macmillan Publishers Limited

                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
                : 25 September 2015
                : 04 December 2015
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