TY - JOUR
T1 - Digging into the low molecular weight peptidome with the OligoNet web server
AU - Liu, Youzhong
AU - Forcisi, Sara
AU - Lucio, Marianna
AU - Harir, Mourad
AU - Bahut, Florian
AU - Deleris-Bou, Magali
AU - Krieger-Weber, Sibylle
AU - Gougeon, Régis D.
AU - Alexandre, Hervé
AU - Schmitt-Kopplin, Philippe
N1 - Publisher Copyright:
© 2017 The Author(s).
PY - 2017/12/1
Y1 - 2017/12/1
N2 - Bioactive peptides play critical roles in regulating many biological processes. Recently, natural short peptides biomarkers are drawing significant attention and are considered as "hidden treasure" of drug candidates. High resolution and high mass accuracy provided by mass spectrometry (MS)-based untargeted metabolomics would enable the rapid detection and wide coverage of the low-molecular-weight peptidome. However, translating unknown masses (<1 500 Da) into putative peptides is often limited due to the lack of automatic data processing tools and to the limit of peptide databases. The web server OligoNet responds to this challenge by attempting to decompose each individual mass into a combination of amino acids out of metabolomics datasets. It provides an additional network-based data interpretation named "Peptide degradation network" (PDN), which unravels interesting relations between annotated peptides and generates potential functional patterns. The ab initio PDN built from yeast metabolic profiling data shows a great similarity with well-known metabolic networks, and could aid biological interpretation. OligoNet allows also an easy evaluation and interpretation of annotated peptides in systems biology, and is freely accessible at https://daniellyz200608105.shinyapps.io/OligoNet/.
AB - Bioactive peptides play critical roles in regulating many biological processes. Recently, natural short peptides biomarkers are drawing significant attention and are considered as "hidden treasure" of drug candidates. High resolution and high mass accuracy provided by mass spectrometry (MS)-based untargeted metabolomics would enable the rapid detection and wide coverage of the low-molecular-weight peptidome. However, translating unknown masses (<1 500 Da) into putative peptides is often limited due to the lack of automatic data processing tools and to the limit of peptide databases. The web server OligoNet responds to this challenge by attempting to decompose each individual mass into a combination of amino acids out of metabolomics datasets. It provides an additional network-based data interpretation named "Peptide degradation network" (PDN), which unravels interesting relations between annotated peptides and generates potential functional patterns. The ab initio PDN built from yeast metabolic profiling data shows a great similarity with well-known metabolic networks, and could aid biological interpretation. OligoNet allows also an easy evaluation and interpretation of annotated peptides in systems biology, and is freely accessible at https://daniellyz200608105.shinyapps.io/OligoNet/.
UR - http://www.scopus.com/inward/record.url?scp=85029495160&partnerID=8YFLogxK
U2 - 10.1038/s41598-017-11786-w
DO - 10.1038/s41598-017-11786-w
M3 - Article
C2 - 28916823
AN - SCOPUS:85029495160
VL - 7
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 11692
ER -