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Public Library of Science, PLoS ONE, 5(8), p. e64125, 2013

DOI: 10.1371/journal.pone.0064125

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Integrative Approach Reveals Composition of Endoparasitoid Wasp Venoms

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Preprint: archiving allowed
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Postprint: archiving allowed
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Data provided by SHERPA/RoMEO

Abstract

The fruit fly Drosophila melanogaster and its endoparasitoid wasps are a developing model system for interactions between host immune responses and parasite virulence mechanisms. In this system, wasps use diverse venom cocktails to suppress the conserved fly cellular encapsulation response. Although numerous genetic tools allow detailed characterization of fly immune genes, lack of wasp genomic information has hindered characterization of the parasite side of the interaction. Here, we use high-throughput nucleic acid and amino acid sequencing methods to describe the venoms of two related Drosophila endoparasitoids with distinct infection strategies, Leptopilina boulardi and L. heterotoma. Using RNA-seq, we assembled and quantified libraries of transcript sequences from female wasp abdomens. Next, we used mass spectrometry to sequence peptides derived from dissected venom gland lumens. We then mapped the peptide spectral data against the abdomen transcriptomes to identify a set of putative venom genes for each wasp species. Our approach captured the three venom genes previously characterized in L. boulardi by traditional cDNA cloning methods as well as numerous new venom genes that were subsequently validated by a combination of RT-PCR, blast comparisons, and secretion signal sequence search. Overall, 129 proteins were found to comprise L. boulardi venom and 176 proteins were found to comprise L. heterotoma venom. We found significant overlap in L. boulardi and L. heterotoma venom composition but also distinct differences that may underlie their unique infection strategies. Our joint transcriptomic-proteomic approach for endoparasitoid wasp venoms is generally applicable to identification of functional protein subsets from any non-genome sequenced organism.