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Status: Bibliographieeintrag

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Verfasst von:Hayakawa, Eisuke [VerfasserIn]   i
 Watanabe, Hiroshi [VerfasserIn]   i
 Menschaert, Gerben [VerfasserIn]   i
 Holstein, Thomas W. [VerfasserIn]   i
 Baggerman, Geert [VerfasserIn]   i
 Schoofs, Liliane [VerfasserIn]   i
Titel:A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis
Verf.angabe:Eisuke Hayakawa, Hiroshi Watanabe, Gerben Menschaert, Thomas W. Holstein, Geert Baggerman, Liliane Schoofs
E-Jahr:2019
Jahr:23 September 2019
Umfang:20 S.
Fussnoten:Gesehen am 09.04.2020
Titel Quelle:Enthalten in: PLOS ONE
Ort Quelle:San Francisco, California, US : PLOS, 2006
Jahr Quelle:2019
Band/Heft Quelle:14(2019,9) Artikel-Nummre e0215185, 20 Seiten
ISSN Quelle:1932-6203
Abstract:Neuropeptides are a class of bioactive peptides shown to be involved in various physiological processes, including metabolism, development, and reproduction. Although neuropeptide candidates have been predicted from genomic and transcriptomic data, comprehensive characterization of neuropeptide repertoires remains a challenge owing to their small size and variable sequences. De novo prediction of neuropeptides from genome or transcriptome data is difficult and usually only efficient for those peptides that have identified orthologs in other animal species. Recent peptidomics technology has enabled systematic structural identification of neuropeptides by using the combination of liquid chromatography and tandem mass spectrometry. However, reliable identification of naturally occurring peptides using a conventional tandem mass spectrometry approach, scanning spectra against a protein database, remains difficult because a large search space must be scanned due to the absence of a cleavage enzyme specification. We developed a pipeline consisting of in silico prediction of candidate neuropeptides followed by peptide-spectrum matching. This approach enables highly sensitive and reliable neuropeptide identification, as the search space for peptide-spectrum matching is highly reduced. Nematostella vectensis is a basal eumetazoan with one of the most ancient nervous systems. We scanned the Nematostella protein database for sequences displaying structural hallmarks typical of eumetazoan neuropeptide precursors, including amino- and carboxyterminal motifs and associated modifications. Peptide-spectrum matching was performed against a dataset of peptides that are cleaved in silico from these putative peptide precursors. The dozens of newly identified neuropeptides display structural similarities to bilaterian neuropeptides including tachykinin, myoinhibitory peptide, and neuromedin-U/pyrokinin, suggesting these neuropeptides occurred in the eumetazoan ancestor of all animal species.
DOI:doi:10.1371/journal.pone.0215185
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext ; Verlag: https://doi.org/10.1371/journal.pone.0215185
 Volltext: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0215185
 DOI: https://doi.org/10.1371/journal.pone.0215185
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Amidation
 Animal evolution
 Database searching
 Protein extraction
 Sequence databases
 Sequence motif analysis
 Sequence similarity searching
 Signal peptides
K10plus-PPN:169432561X
Verknüpfungen:→ Zeitschrift

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