Plant neighborhood influences colonization of Brassicaceae by specialist and generalist aphids

A plant's own characteristics, but also those of its neighbors, might have an impact on its probability of being colonized by herbivorous insects. A plant might be less colonized and experience associational resistance when it grows near repellent neighbors. In contrast, it might be more colonized and experience associational susceptibility near attractive neighbors. To date, mechanisms that drive associational defense are not really understood. In order to gain insights into the occurrence of associational resistance versus associational susceptibility under field conditions, we conducted an experiment to determine the influence of neighboring plants on the colonization of a focal plant by aphids. The focal plant was always Brassica oleracea. The neighbors were B. oleracea (control), B. napus, B. nigra, or Solanum lycopersicum, which represent contrasting levels of physical and chemical defenses. The focal plant, B. oleracea, was more colonized by the specialist aphid Brevicoryne brassicae, and experienced associational susceptibility when it was surrounded by B. nigra or B. napus. In contrast, B. oleracea was less colonized by the generalist aphid Myzus persicae, and experienced associational resistance when it was surrounded by S. lycopersicum, B. nigra or B. napus. Neighboring plants had no significant impact on host plant choice by the generalist aphid Macrosiphum euphorbiae. In conclusion, attraction or repulsion of the specialist aphid B. brassicae and the generalist aphid M. persicae by B. nigra, B. napus, and S. lycopersicum resulted in associational susceptibility or associational resistance for B. oleracea.     

A short motif in Drosophila SECIS Binding Protein 2 provides differential binding affinity to SECIS RNA hairpins

Selenoproteins contain the amino acid selenocysteine which is encoded by a UGA Sec codon. Recoding UGA Sec requires a complex mechanism, comprising the cis-acting SECIS RNA hairpin in the 3′UTR of selenoprotein mRNAs, and trans-acting factors. Among these, the SECIS Binding Protein 2 (SBP2) is central to the mechanism. SBP2 has been so far functionally characterized only in rats and humans. In this work, we report the characterization of the Drosophila melanogaster SBP2 (dSBP2). Despite its shorter length, it retained the same selenoprotein synthesis-promoting capabilities as the mammalian counterpart. However, a major difference resides in the SECIS recognition pattern: while human SBP2 (hSBP2) binds the distinct form 1 and 2 SECIS RNAs with similar affinities, dSBP2 exhibits high affinity toward form 2 only. In addition, we report the identification of a K (lysine)-rich domain in all SBP2s, essential for SECIS and 60S ribosomal subunit binding, differing from the well-characterized L7Ae RNA-binding domain. Swapping only five amino acids between dSBP2 and hSBP2 in the K-rich domain conferred reversed SECIS-binding properties to the proteins, thus unveiling an important sequence for form 1 binding.     

A comparison of random sequence reads versus 16S rDNA sequences for estimating the biodiversity of a metagenomic library

The construction of metagenomic libraries has permitted the study of microorganisms resistant to isolation and the analysis of 16S rDNA sequences has been used for over two decades to examine bacterial biodiversity. Here, we show that the analysis of random sequence reads (RSRs) instead of 16S is a suitable shortcut to estimate the biodiversity of a bacterial community from metagenomic libraries. We generated 10 010 RSRs from a metagenomic library of microorganisms found in human faecal samples. Then searched them using the program BLASTN against a prokaryotic sequence database to assign a taxon to each RSR. The results were compared with those obtained by screening and analysing the clones containing 16S rDNA sequences in the whole library. We found that the biodiversity observed by RSR analysis is consistent with that obtained by 16S rDNA. We also show that RSRs are suitable to compare the biodiversity between different metagenomic libraries. RSRs can thus provide a good estimate of the biodiversity of a metagenomic library and, as an alternative to 16S, this approach is both faster and cheaper.     

Automatic evaluation of protein sequence functional patterns

A procedure that automatically provides an evaluation of thediagnostic ability of a protein sequence functional patternis described. The procedure relies on the identification ofthe closest definable set in terms of a (protein sequence) databasefunctional annotation to the set of database instances containinga given pattern. Assuming annotation correctness and completenessin the protein sequence database, the degree of statisticalassociation between these sets provides an appropriate measureof the diagnostic ability of the pattern. An experimental implementationof the procedure, using the NBRF/PIR protein database, has beenapplied to a diverse collection of published sequence patterns.Results obtained reveal that frequently it is not possible todefine (in NBRF/PIR database terminology) the set of databaseinstances containing a given pattern, suggesting either lackof pattern diagnostic ability or protein database annotationincompleteness and/or inconsistencies. Received on November 30, 1989; accepted on July 20, 1990     

Composition and evolution of the vertebrate and mammalian selenoproteomes

Background

Selenium is an essential trace element in mammals due to its presence in proteins in the form of selenocysteine (Sec). Human genome codes for 25 Sec-containing protein genes, and mouse and rat genomes for 24.

Methodology/Principal Findings

We characterized the selenoproteomes of 44 sequenced vertebrates by applying gene prediction and phylogenetic reconstruction methods, supplemented with the analyses of gene structures, alternative splicing isoforms, untranslated regions, SECIS elements, and pseudogenes. In total, we detected 45 selenoprotein subfamilies. 28 of them were found in mammals, and 41 in bony fishes. We define the ancestral vertebrate (28 proteins) and mammalian (25 proteins) selenoproteomes, and describe how they evolved along lineages through gene duplication (20 events), gene loss (10 events) and replacement of Sec with cysteine (12 events). We show that an intronless selenophosphate synthetase 2 gene evolved in early mammals and replaced functionally the original multiexon gene in placental mammals, whereas both genes remain in marsupials. Mammalian thioredoxin reductase 1 and thioredoxin-glutathione reductase evolved from an ancestral glutaredoxin-domain containing enzyme, still present in fish. Selenoprotein V and GPx6 evolved specifically in placental mammals from duplications of SelW and GPx3, respectively, and GPx6 lost Sec several times independently. Bony fishes were characterized by duplications of several selenoprotein families (GPx1, GPx3, GPx4, Dio3, MsrB1, SelJ, SelO, SelT, SelU1, and SelW2). Finally, we report identification of new isoforms for several selenoproteins and describe unusually conserved selenoprotein pseudogenes.

Conclusions/Significance

This analysis represents the first comprehensive survey of the vertebrate and mammal selenoproteomes, and depicts their evolution along lineages. It also provides a wealth of information on these selenoproteins and their forms.     

SECISearch3 and Seblastian: new tools for prediction of SECIS elements and selenoproteins

Selenoproteins are proteins containing an uncommon amino acid selenocysteine (Sec). Sec is inserted by a specific translational machinery that recognizes a stem-loop structure, the SECIS element, at the 3′ UTR of selenoprotein genes and recodes a UGA codon within the coding sequence. As UGA is normally a translational stop signal, selenoproteins are generally misannotated and designated tools have to be developed for this class of proteins. Here, we present two new computational methods for selenoprotein identification and analysis, which we provide publicly through the web servers at http://gladyshevlab.org/SelenoproteinPredictionServer or http://seblastian.crg.es. SECISearch3 replaces its predecessor SECISearch as a tool for prediction of eukaryotic SECIS elements. Seblastian is a new method for selenoprotein gene detection that uses SECISearch3 and then predicts selenoprotein sequences encoded upstream of SECIS elements. Seblastian is able to both identify known selenoproteins and predict new selenoproteins. By applying these tools to diverse eukaryotic genomes, we provide a ranked list of newly predicted selenoproteins together with their annotated cysteine-containing homologues. An analysis of a representative candidate belonging to the AhpC family shows how the use of Sec in this protein evolved in bacterial and eukaryotic lineages.