Position-specific scoring matrix and hidden Markov model complement each other for the prediction of conopeptide superfamilies

Koua, Dominique; Laht, Silja; Kaplinski, Lauris; Stöcklin, Reto; Remm, Maido; Favreau, Philippe; Lisacek, Frédérique

doi:10.1016/j.bbapap.2012.12.015

Cited by 12 publications

(19 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to retrieve putative toxin sequences, Hidden Markov Model (HMM) profiles were built for each structural family [30], based on cysteine-rich spider toxins referenced in Arachnoserver, a public domain database [23]. Low confidence sequences, represented by a low number of reads, or containing a frameshift or misassembly, were removed (a minimum of 10 reads was set as cutoff).…”

Section: Resultsmentioning

confidence: 99%

Peptidomic and transcriptomic profiling of four distinct spider venoms

et al. 2017

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Resultsmentioning

confidence: 99%

Peptidomic and transcriptomic profiling of four distinct spider venoms

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…Based on these theories and as a solution for gene annotation, profile-based alignments are more credible since their arithmetic has been based on the position-scoring matrices of conservative sites and further applied on a few studies for analyzing venom gland transcriptomes [7,46,47,48]. Profile-hidden Markov models (pHMMS) have been recently used to identify toxin transcripts in several cone snails and fish transcriptomes [7,46,47,49,50,51]. …”

Section: Venom-gland Transcriptomicsmentioning

confidence: 99%

From Marine Venoms to Drugs: Efficiently Supported by a Combination of Transcriptomics and Proteomics

et al. 2017

View full text Add to dashboard Cite

The potential of marine natural products to become new drugs is vast; however, research is still in its infancy. The chemical and biological diversity of marine toxins is immeasurable and as such an extraordinary resource for the discovery of new drugs. With the rapid development of next-generation sequencing (NGS) and liquid chromatography–tandem mass spectrometry (LC-MS/MS), it has been much easier and faster to identify more toxins and predict their functions with bioinformatics pipelines, which pave the way for novel drug developments. Here we provide an overview of related bioinformatics pipelines that have been supported by a combination of transcriptomics and proteomics for identification and function prediction of novel marine toxins.

show abstract

“…Sequences coding for toxins were detected using GeneWise (EMBL-EBI version 2.4.1 - (Birney et al, 2004)) and HMMER2 models based on public sequences of conotoxins (ConoServer and UniProt). Signal sequences in toxins were identified using an in-house (Koua et al, 2013).…”

Section: Venom Gland Mrna Transcriptomic Sequencingmentioning

confidence: 99%

When everything converges: Integrative taxonomy with shell, DNA and venomic data reveals Conus conco, a new species of cone snails (Gastropoda: Conoidea)

Puillandre

Stöcklin

Favreau

et al. 2014

Molecular Phylogenetics and Evolution

Self Cite

View full text Add to dashboard Cite

Cone snails have long been studied both by taxonomists for the diversity of their shells and by biochemists for the potential therapeutic applications of their toxins. Phylogenetic approaches have revealed that different lineages of Conus evolved divergent venoms, a property that is exploited to enhance the discovery of new conotoxins, but is rarely used in taxonomy. Specimens belonging to the Indo-West Pacific Conus lividus species complex were analyzed using phenetic and phylogenetic methods based on shell morphology, COI and 28S rRNA gene sequences and venom mRNA expression and protein composition. All methods converged to reveal a new species, C. conco n. sp. (described in Supplementary data), restricted to the Marquesas Islands, where it diverged recently (∼3mya) from C. lividus. The geographical distribution of C. conco and C. lividus and their phylogenetic relationships suggest that the two species diverged in allopatry. Furthermore, the diversity of the transcript sequences and toxin molecular masses suggest that C. conco evolved unique toxins, presumably in response to new selective pressure, such as the availability of new preys and ecological niches. Furthermore, this new species evolved new transcripts giving rise to original toxin structures, probably each carrying specific biological activity.

show abstract

Position-specific scoring matrix and hidden Markov model complement each other for the prediction of conopeptide superfamilies

Cited by 12 publications

References 35 publications

Peptidomic and transcriptomic profiling of four distinct spider venoms

Peptidomic and transcriptomic profiling of four distinct spider venoms

From Marine Venoms to Drugs: Efficiently Supported by a Combination of Transcriptomics and Proteomics

When everything converges: Integrative taxonomy with shell, DNA and venomic data reveals Conus conco, a new species of cone snails (Gastropoda: Conoidea)

Contact Info

Product

Resources

About