On Mass Ambiguities in High-Resolution Shotgun Lipidomics

Area of Science:

• Analytical Chemistry
• Biochemistry
• Metabolomics

Background:

• Lipidomics aims to identify numerous lipid species in biological samples.
• Unambiguous lipid identification is challenging due to the vast combinatorial search space and mass ambiguities, especially in direct-injection shotgun experiments lacking orthogonal separation.
• Mass ambiguities arise from similar masses of different lipid species, adducts, and isotopes.

Purpose of the Study:

• To develop a comprehensive rule set for identifying and resolving mass ambiguities in mass spectrometry-based lipidomics.
• To account for mass analyzer resolving power and common adducts/isotopes in mass ambiguity analysis.
• To provide guidelines for experimentalists and software developers to enhance lipid identification rigor.

Main Methods:

• Generated a comprehensive rule set for mass ambiguities using lipid databases.
• Incorporated mass analyzer resolving power and its decay into the rule set.
• Accounted for common adduct species and isotopic peaks in the analysis.
• Identified and ranked lipid classes based on their propensity to cause ambiguities.

Main Results:

• A novel rule set for mass ambiguities in lipidomics was generated, considering instrument resolution and adducts/isotopes.
• Known and novel mass ambiguities were identified in high- and ultrahigh-resolution mass spectrometry data.
• Lipid classes were ranked by their likelihood of causing mass ambiguities.
• The significant role of adducts and isotopes in creating both perfect and resolvable mass overlaps was demonstrated.

Conclusions:

• The developed rule set aids in achieving more solid lipid identifications in mass spectrometry (MS) and MS/MS.
• Findings offer implications for selecting internal standards, mass calibration peaks, and optimizing instrument resolution and sample preparation.
• This work provides a valuable resource for researchers, particularly those new to lipidomics, to navigate and account for mass ambiguities.