Evidence map›Paper›PMID 28306751›Full record

ArticlePloS one2017

Peptidomic and transcriptomic profiling of four distinct spider venoms.

Vera Oldrati, Dominique Koua, Pierre-Marie Allard, Nicolas Hulo, Miriam Arrell, Wolfgang Nentwig, Frédérique Lisacek, Jean-Luc Wolfender, Lucia Kuhn-Nentwig, Reto Stöcklin

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. Current Challenges and Future Directions in Peptidomics.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Toxinology in the proteomics era: a review on arachnid venom proteomics.The journal of venomous animals and toxins including tropical diseases · 2022
    Article
  8. De Novo Transcriptome Analysis of the Venom ofMolecules (Basel, Switzerland) · 2021
    Article
  9. Widow spiders in the New World: a review onThe journal of venomous animals and toxins including tropical diseases · 2021
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Vera OldratiAtheris SA, Chemin d'Alcire 1, Plan-les-Ouates, Geneva, Switzerland.
Dominique KouaAtheris SA, Chemin d'Alcire 1, Plan-les-Ouates, Geneva, Switzerland.
Pierre-Marie AllardSchool of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, 1, Rue Michel-Servet, Geneva 4, Switzerland.
Nicolas HuloUniversity of Geneva, CMU, 1, Rue Michel Servet, Geneva 4, Switzerland.
Miriam ArrellAtheris SA, Chemin d'Alcire 1, Plan-les-Ouates, Geneva, Switzerland.
Wolfgang NentwigUniversity of Bern, Institute of Ecology and Evolution, 6, Baltzerstrasse, Bern, Switzerland.
Frédérique LisacekUniversity of Geneva, CMU, 1, Rue Michel Servet, Geneva 4, Switzerland.
Jean-Luc WolfenderSchool of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, 1, Rue Michel-Servet, Geneva 4, Switzerland.
Lucia Kuhn-NentwigUniversity of Bern, Institute of Ecology and Evolution, 6, Baltzerstrasse, Bern, Switzerland.
Reto StöcklinAtheris SA, Chemin d'Alcire 1, Plan-les-Ouates, Geneva, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Venom based research is exploited to find novel candidates for the development of innovative pharmacological tools, drug candidates and new ingredients for cosmetic and agrochemical industries. Moreover, venomics, as a well-established approach in systems biology, helps to elucidate the genetic mechanisms of the production of such a great molecular biodiversity. Today the advances made in the proteomics, transcriptomics and bioinformatics fields, favor venomics, allowing the in depth study of complex matrices and the elucidation even of minor compounds present in minute biological samples. The present study illustrates a rapid and efficient method developed for the elucidation of venom composition based on NextGen mRNA sequencing of venom glands and LC-MS/MS venom proteome profiling. The analysis of the comprehensive data obtained was focused on cysteine rich peptide toxins from four spider species originating from phylogenetically distant families for comparison purposes. The studied species were Heteropoda davidbowie (Sparassidae), Poecilotheria formosa (Theraphosidae), Viridasius fasciatus (Viridasiidae) and Latrodectus mactans (Theridiidae). This led to a high resolution profiling of 284 characterized cysteine rich peptides, 111 of which belong to the Inhibitor Cysteine Knot (ICK) structural motif. The analysis of H. davidbowie venom revealed a high richness in term of venom diversity: 95 peptide sequences were identified; out of these, 32 peptides presented the ICK structural motif and could be classified in six distinct families. The profiling of P. formosa venom highlighted the presence of 126 peptide sequences, with 52 ICK toxins belonging to three structural distinct families. V. fasciatus venom was shown to contain 49 peptide sequences, out of which 22 presented the ICK structural motif and were attributed to five families. The venom of L. mactans, until now studied for its large neurotoxins (Latrotoxins), revealed the presence of 14 cysteine rich peptides, out of which five were ICK toxins belonging to the CSTX superfamily. This in depth profiling of distinct ICK peptide families identified across the four spider species highlighted the high conservation of these neurotoxins among spider families.

Indexed as

TranscriptomeChromatography, LiquidPeptidesSpider VenomsTandem Mass SpectrometryPeptidesSpider Venoms

Identifiers

PMID28306751
PMCPMC5357004

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.