A Kaufmann1, S Walker1, G Mol1. 1. Official Food Control Authority, Fehrenstrasse 15, 8032, Zürich, Switzerland.
Abstract
RATIONALE: Elucidation of the elemental compositions of unknown compounds (e.g., in metabolomics) generally relies on the availability of accurate masses and isotopic ratios. This study focuses on the information provided by the abundance ratio within a product ion pair (monoisotopic versus the first isotopic peak) when isolating and fragmenting the first isotopic ion (first isotopic mass spectrum) of the precursor. METHODS: This process relies on the capability of the quadrupole within the Q Orbitrap instrument to isolate a very narrow mass window. Selecting only the first isotopic peak (first isotopic mass spectrum) leads to the observation of a unique product ion pair. The lighter ion within such an isotopologue pair is monoisotopic, while the heavier ion contains a single carbon isotope. The observed abundance ratio is governed by the percentage of carbon atoms lost during the fragmentation and can be described by a hypergeometric distribution. RESULTS: The observed carbon isotopologue abundance ratio (product ion isotopologue pattern) gives reliable information regarding the percentage of carbon atoms lost in the fragmentation process. It therefore facilitates the elucidation of the involved precursor and product ions. Unlike conventional isotopic abundances, the product ion isotopologue pattern is hardly affected by isobaric interferences. Furthermore, the appearance of these pairs greatly aids in cleaning up a 'matrix-contaminated' product ion spectrum. CONCLUSIONS: The product ion isotopologue pattern is a valuable tool for structural elucidation. It increases confidence in results and permits structural elucidations for heavier ions. This tool is also very useful in elucidating the elemental composition of product ions. Such information is highly valued in the field of multi-residue analysis, where the accurate mass of product ions is required for the confirmation process.
RATIONALE: Elucidation of the elemental compositions of unknown compounds (e.g., in metabolomics) generally relies on the availability of accurate masses and isotopic ratios. This study focuses on the information provided by the abundance ratio within a product ion pair (monoisotopic versus the first isotopic peak) when isolating and fragmenting the first isotopic ion (first isotopic mass spectrum) of the precursor. METHODS: This process relies on the capability of the quadrupole within the Q Orbitrap instrument to isolate a very narrow mass window. Selecting only the first isotopic peak (first isotopic mass spectrum) leads to the observation of a unique product ion pair. The lighter ion within such an isotopologue pair is monoisotopic, while the heavier ion contains a single carbon isotope. The observed abundance ratio is governed by the percentage of carbon atoms lost during the fragmentation and can be described by a hypergeometric distribution. RESULTS: The observed carbon isotopologue abundance ratio (product ion isotopologue pattern) gives reliable information regarding the percentage of carbon atoms lost in the fragmentation process. It therefore facilitates the elucidation of the involved precursor and product ions. Unlike conventional isotopic abundances, the product ion isotopologue pattern is hardly affected by isobaric interferences. Furthermore, the appearance of these pairs greatly aids in cleaning up a 'matrix-contaminated' product ion spectrum. CONCLUSIONS: The product ion isotopologue pattern is a valuable tool for structural elucidation. It increases confidence in results and permits structural elucidations for heavier ions. This tool is also very useful in elucidating the elemental composition of product ions. Such information is highly valued in the field of multi-residue analysis, where the accurate mass of product ions is required for the confirmation process.
Authors: Daniel D Snow; David A Cassada; Megan L Larsen; Noelle A Mware; Xu Li; Matteo D'Alessio; Yun Zhang; J Brett Sallach Journal: Water Environ Res Date: 2017-10-01 Impact factor: 1.946