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Dominique Koua
Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, CH-3012 Bern, Switzerland.

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Journal article
Published: 19 March 2019 in Toxins
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Most knowledge of spider venom concerns neurotoxins acting on ion channels, whereas proteins and their significance for the envenomation process are neglected. The here presented comprehensive analysis of the venom gland transcriptome and proteome of Cupiennius salei focusses on proteins and cysteine-containing peptides and offers new insight into the structure and function of spider venom, here described as the dual prey-inactivation strategy. After venom injection, many enzymes and proteins, dominated by α-amylase, angiotensin-converting enzyme, and cysteine-rich secretory proteins, interact with main metabolic pathways, leading to a major disturbance of the cellular homeostasis. Hyaluronidase and cytolytic peptides destroy tissue and membranes, thus supporting the spread of other venom compounds. We detected 81 transcripts of neurotoxins from 13 peptide families, whereof two families comprise 93.7% of all cysteine-containing peptides. This raises the question of the importance of the other low-expressed peptide families. The identification of a venom gland-specific defensin-like peptide and an aga-toxin-like peptide in the hemocytes offers an important clue on the recruitment and neofunctionalization of body proteins and peptides as the origin of toxins.

ACS Style

Lucia Kuhn-Nentwig; Nicolas Langenegger; Manfred Heller; Dominique Koua; Wolfgang Nentwig. The Dual Prey-Inactivation Strategy of Spiders-In-Depth Venomic Analysis of Cupiennius salei. Toxins 2019, 11, 167 .

AMA Style

Lucia Kuhn-Nentwig, Nicolas Langenegger, Manfred Heller, Dominique Koua, Wolfgang Nentwig. The Dual Prey-Inactivation Strategy of Spiders-In-Depth Venomic Analysis of Cupiennius salei. Toxins. 2019; 11 (3):167.

Chicago/Turabian Style

Lucia Kuhn-Nentwig; Nicolas Langenegger; Manfred Heller; Dominique Koua; Wolfgang Nentwig. 2019. "The Dual Prey-Inactivation Strategy of Spiders-In-Depth Venomic Analysis of Cupiennius salei." Toxins 11, no. 3: 167.

Journal article
Published: 08 August 2017 in Toxins
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Spider venoms are rich cocktails of bioactive peptides, proteins, and enzymes that are being intensively investigated over the years. In order to provide a better comprehension of that richness, we propose a three-level family classification system for spider venom components. This classification is supported by an exhaustive set of 219 new profile hidden Markov models (HMMs) able to attribute a given peptide to its precise peptide type, family, and group. The proposed classification has the advantages of being totally independent from variable spider taxonomic names and can easily evolve. In addition to the new classifiers, we introduce and demonstrate the efficiency of hmmcompete, a new standalone tool that monitors HMM-based family classification and, after post-processing the result, reports the best classifier when multiple models produce significant scores towards given peptide queries. The combined used of hmmcompete and the new spider venom component-specific classifiers demonstrated 96% sensitivity to properly classify all known spider toxins from the UniProtKB database. These tools are timely regarding the important classification needs caused by the increasing number of peptides and proteins generated by transcriptomic projects.

ACS Style

Dominique Koua; Lucia Kuhn-Nentwig. Spider Neurotoxins, Short Linear Cationic Peptides and Venom Protein Classification Improved by an Automated Competition between Exhaustive Profile HMM Classifiers. Toxins 2017, 9, 245 .

AMA Style

Dominique Koua, Lucia Kuhn-Nentwig. Spider Neurotoxins, Short Linear Cationic Peptides and Venom Protein Classification Improved by an Automated Competition between Exhaustive Profile HMM Classifiers. Toxins. 2017; 9 (8):245.

Chicago/Turabian Style

Dominique Koua; Lucia Kuhn-Nentwig. 2017. "Spider Neurotoxins, Short Linear Cationic Peptides and Venom Protein Classification Improved by an Automated Competition between Exhaustive Profile HMM Classifiers." Toxins 9, no. 8: 245.