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      Identification of the main venom protein components of Aphidius ervi, a parasitoid wasp of the aphid model Acyrthosiphon pisum

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          Abstract

          Background

          Endoparasitoid wasps are important natural enemies of the widely distributed aphid pests and are mainly used as biological control agents. However, despite the increased interest on aphid interaction networks, only sparse information is available on the factors used by parasitoids to modulate the aphid physiology. Our aim was here to identify the major protein components of the venom injected at oviposition by Aphidius ervi to ensure successful development in its aphid host, Acyrthosiphon pisum.

          Results

          A combined large-scale transcriptomic and proteomic approach allowed us to identify 16 putative venom proteins among which three γ-glutamyl transpeptidases (γ-GTs) were by far the most abundant. Two of the γ-GTs most likely correspond to alleles of the same gene, with one of these alleles previously described as involved in host castration. The third γ-GT was only distantly related to the others and may not be functional owing to the presence of mutations in the active site. Among the other abundant proteins in the venom, several were unique to A. ervi such as the molecular chaperone endoplasmin possibly involved in protecting proteins during their secretion and transport in the host. Abundant transcripts encoding three secreted cystein-rich toxin-like peptides whose function remains to be explored were also identified.

          Conclusions

          Our data further support the role of γ-GTs as key players in A. ervi success on aphid hosts. However, they also evidence that this wasp venom is a complex fluid that contains diverse, more or less specific, protein components. Their characterization will undoubtedly help deciphering parasitoid-aphid and parasitoid-aphid-symbiont interactions. Finally, this study also shed light on the quick evolution of venom components through processes such as duplication and convergent recruitment of virulence factors between unrelated organisms.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1471-2164-15-342) contains supplementary material, which is available to authorized users.

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          Most cited references59

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          TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets.

          TGICL is a pipeline for analysis of large Expressed Sequence Tags (EST) and mRNA databases in which the sequences are first clustered based on pairwise sequence similarity, and then assembled by individual clusters (optionally with quality values) to produce longer, more complete consensus sequences. The system can run on multi-CPU architectures including SMP and PVM.
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            • Record: found
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            A new generation of homology search tools based on probabilistic inference.

            Many theoretical advances have been made in applying probabilistic inference methods to improve the power of sequence homology searches, yet the BLAST suite of programs is still the workhorse for most of the field. The main reason for this is practical: BLAST's programs are about 100-fold faster than the fastest competing implementations of probabilistic inference methods. I describe recent work on the HMMER software suite for protein sequence analysis, which implements probabilistic inference using profile hidden Markov models. Our aim in HMMER3 is to achieve BLAST's speed while further improving the power of probabilistic inference based methods. HMMER3 implements a new probabilistic model of local sequence alignment and a new heuristic acceleration algorithm. Combined with efficient vector-parallel implementations on modern processors, these improvements synergize. HMMER3 uses more powerful log-odds likelihood scores (scores summed over alignment uncertainty, rather than scoring a single optimal alignment); it calculates accurate expectation values (E-values) for those scores without simulation using a generalization of Karlin/Altschul theory; it computes posterior distributions over the ensemble of possible alignments and returns posterior probabilities (confidences) in each aligned residue; and it does all this at an overall speed comparable to BLAST. The HMMER project aims to usher in a new generation of more powerful homology search tools based on probabilistic inference methods.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Silver stain for proteins in polyacrylamide gels: a modified procedure with enhanced uniform sensitivity.

                Bookmark

                Author and article information

                Contributors
                colinet@sophia.inra.fr
                caroline.anselme@u-picardie.fr
                deleury@sophia.inra.fr
                dmancini@unina.it
                poulain@genoscope.cns.fr
                cdossat@genoscope.cns.fr
                maya.belghazi@univ-amu.fr
                Sophie.Tares@sophia.inra.fr
                f.pennacchio@unina.it
                Marylene.Poirie@sophia.inra.fr
                Jean-luc.Gatti@sophia.inra.fr
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                6 May 2014
                6 May 2014
                2014
                : 15
                : 1
                : 342
                Affiliations
                [ ]INRA, ISA, UMR 1355, Evolution et Spécificité des Interactions Multitrophiques (ESIM), Sophia Antipolis, 06903 France
                [ ]Université Nice Sophia Antipolis, ISA, Sophia Antipolis, 06903 France
                [ ]CNRS, ISA, UMR 7254, Sophia Antipolis, 06903 France
                [ ]Dipartimento di Agraria, Laboratorio di Entomologia “E. Tremblay”, Università degli Studi di Napoli “Federico II”, Portici, Napoli, Italy
                [ ]Commissariat à l’Energie Atomique (CEA), Institut de Génomique (IG), Génoscope, Evry, France
                [ ]Faculté de Médecine - Secteur Nord, CNRS, Aix-Marseille Université, UMR 7286, CRN2M, Centre d’Analyses Protéomiques de Marseille (CAPM), 51, bd Dramard, Marseille, France
                [ ]CNRS FRE 3498 EDYSAN, Bio-écologie des Insectes Phytophages et Entomophages (BIPE), Université de Picardie Jules Verne (UPJV), Amiens, France
                [ ]Evolution and Specificity of Multitrophic Interactions (ESIM), UMR 1355 “Sophia Agrobiotech Institute” (ISA), Institut National de la Recherche Agronomique, INRA PACA, 400 route des Chappes, Sophia Antipolis, 06903 France
                Article
                6064
                10.1186/1471-2164-15-342
                4035087
                24884493
                b7dbd28d-6088-42da-9a4b-5d0734f1bba7
                © Colinet et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 15 January 2014
                : 30 April 2014
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

                Genetics
                parasitoid wasp,aphid,acyrthosiphon pisum,aphidius ervi,venom proteins,virulence,γ-glutamyl transpeptidase,cystein-rich peptides

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