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A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis

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 repe...

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Autores principales: Hayakawa, Eisuke, Watanabe, Hiroshi, Menschaert, Gerben, Holstein, Thomas W., Baggerman, Geert, Schoofs, Liliane
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6756747/
https://www.ncbi.nlm.nih.gov/pubmed/31545805
http://dx.doi.org/10.1371/journal.pone.0215185
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author Hayakawa, Eisuke
Watanabe, Hiroshi
Menschaert, Gerben
Holstein, Thomas W.
Baggerman, Geert
Schoofs, Liliane
author_facet Hayakawa, Eisuke
Watanabe, Hiroshi
Menschaert, Gerben
Holstein, Thomas W.
Baggerman, Geert
Schoofs, Liliane
author_sort Hayakawa, Eisuke
collection PubMed
description 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.
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spelling pubmed-67567472019-10-04 A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis Hayakawa, Eisuke Watanabe, Hiroshi Menschaert, Gerben Holstein, Thomas W. Baggerman, Geert Schoofs, Liliane PLoS One Research Article 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. Public Library of Science 2019-09-23 /pmc/articles/PMC6756747/ /pubmed/31545805 http://dx.doi.org/10.1371/journal.pone.0215185 Text en © 2019 Hayakawa et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hayakawa, Eisuke
Watanabe, Hiroshi
Menschaert, Gerben
Holstein, Thomas W.
Baggerman, Geert
Schoofs, Liliane
A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis
title A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis
title_full A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis
title_fullStr A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis
title_full_unstemmed A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis
title_short A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis
title_sort combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone nematostella vectensis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6756747/
https://www.ncbi.nlm.nih.gov/pubmed/31545805
http://dx.doi.org/10.1371/journal.pone.0215185
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