Kendrick Mass Defect Approach Combined to NORINE Database for Molecular Formula Assignment of Nonribosomal Peptides

Kendrick map; Mass defect; Molecular formula; Nonribosomal peptides; NORINE; Defects; Mass spectrometry; Molecular mass; Peptides; Database contents; High resolution mass spectrometry; Identification process; Molecular formulae; Nonribosomal peptide; Database systems

Abstract :

[en] The identification of known (dereplication) or unknown nonribosomal peptides (NRPs) produced by microorganisms is a time consuming, expensive, and challenging task where mass spectrometry and nuclear magnetic resonance play a key role. The first step of the identification process always involves the establishment of a molecular formula. Unfortunately, the number of potential molecular formulae increases significantly with higher molecular masses and the lower precision of their measurements. In the present article, we demonstrate that molecular formula assignment can be achieved by a combined approach using the regular Kendrick mass defect (RKMD) and NORINE, the reference curated database of NRPs. We observed that irrespective of the molecular formula, the addition and subtraction of a given atom or atom group always leads to the same RKMD variation and nominal Kendrick mass (NKM). Graphically, these variations translated into a vector mesh can be used to connect an unknown molecule to a known NRP of the NORINE database and establish its molecular formula. We explain and illustrate this concept through the high-resolution mass spectrometry analysis of a commercially available mixture composed of four surfactins. The Kendrick approach enriched with the NORINE database content is a fast, useful, and easy-to-use tool for molecular mass assignment of known and unknown NRP structures. [Figure not available: see fulltext.]. © 2019, American Society for Mass Spectrometry.

Disciplines :

Biochemistry, biophysics & molecular biology

Author, co-author :

Chevalier, M.; Univ. Lille, INRA, ISA, Univ. Artois, Univ. Littoral Côte d’Opale, EA 7394-Institut Charles Viollette (ICV), Lille, F-59000, France

Ricart, E.; Proteome informatics Group, SIB Swiss Institute of Bioinformatics (SIB), and Computer Science Department, University of Geneva, Geneva, Switzerland

Hanozin, Emeline ; Université de Liège - ULiège > Département de chimie (sciences) > Chimie analytique inorganique

Pupin, M.; Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, Lille, F-59000, France, Inria-Lille Nord Europe, Bonsai team, Villeneuve d’Ascq Cedex, F-59655, France

Jacques, Philippe ; Université de Liège - ULiège > Département GxABT > Microbial, food and biobased technologies

Smargiasso, Nicolas ; Mass Spectrometry Laboratory, Molecular Systems - MolSys Research Unit, University of Liège, Liège, Belgium

De Pauw, Edwin ; Université de Liège - ULiège > Département de chimie (sciences) > Chimie analytique inorganique

Lisacek, F.; Proteome informatics Group, SIB Swiss Institute of Bioinformatics (SIB), and Computer Science Department, University of Geneva, Geneva, Switzerland

Leclère, V.; Univ. Lille, INRA, ISA, Univ. Artois, Univ. Littoral Côte d’Opale, EA 7394-Institut Charles Viollette (ICV), Lille, F-59000, France

Flahaut, C.; Univ. Lille, INRA, ISA, Univ. Artois, Univ. Littoral Côte d’Opale, EA 7394-Institut Charles Viollette (ICV), Lille, F-59000, France

Language :

English

Title :

Kendrick Mass Defect Approach Combined to NORINE Database for Molecular Formula Assignment of Nonribosomal Peptides

Publication date :

2019

Journal title :

Journal of the American Society for Mass Spectrometry

ISSN :

1044-0305

eISSN :

1879-1123

Publisher :

Springer

Volume :

Issue :

Pages :

2608-2616

Peer reviewed :

Peer Reviewed verified by ORBi

Funders :

MESRI - Ministère de l’Enseignement supérieur, de la Recherche et de l’Innovation [FR]
MEAE - The Ministry of Economic Affairs and Employment
EU - European Commission
SNI - Swiss Nanoscience Institute

Available on ORBi :

since 12 August 2020

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