Recent progress on analytical platforms for lipidomics has facilitated untargeted approaches and the investigation of low abundant lipid species. As a consequence, the study of modified lipids (epilipidomics) has taken advantage of these technological improvements. Epilipids are formed by a range of enzymatic and non-enzymatic reactions that introduce structural modifications and/or new functional groups in the native molecule. Concerning their biological function, they are known to play crucial roles in physiological and pathological conditions and therefore the untargeted analysis of epilipids has become an important emerging field. Although a number of epilipid species have been extensively studied over the past decades (e.g., eicosanoids), our current knowledge about the entire epilipidome and its biochemistry is still very limited due to experimental and computational obstacles. Epilipids are characterized by low abundance, high structural diversity, high number of isomers/isobars, and display specific fragmentation pattern differing from their unmodified counterparts. Even their annotation is not always univocally defined due to the complexity of the epilipidome. Therefore, software and computational approaches suitable for epilipidomics are highly required to facilitate the analysis of the acquired analytical data, and the number of in silico tools for this purposed is rapidly growing. Here, we review software, in silico approaches and databases currently available for LC-MS-based epilipidomics. The general workflow of an epilipidomics analysis by LC-MS will be briefly described to highlight the specific challenges that computational tools are expected to address. Thus, currently available computational tools for epilipidomics data processing, lipid identification, lipid quantification and data visualization will be described into detail. Finally, a list of databases including epilipids that might find wide application will be reviewed and proposals for future implementations of software will be provided.

Software and Computational Tools for LC-MS-Based Epilipidomics: Challenges and Solutions

Bonciarelli, Stefano;Goracci, Laura
2023

Abstract

Recent progress on analytical platforms for lipidomics has facilitated untargeted approaches and the investigation of low abundant lipid species. As a consequence, the study of modified lipids (epilipidomics) has taken advantage of these technological improvements. Epilipids are formed by a range of enzymatic and non-enzymatic reactions that introduce structural modifications and/or new functional groups in the native molecule. Concerning their biological function, they are known to play crucial roles in physiological and pathological conditions and therefore the untargeted analysis of epilipids has become an important emerging field. Although a number of epilipid species have been extensively studied over the past decades (e.g., eicosanoids), our current knowledge about the entire epilipidome and its biochemistry is still very limited due to experimental and computational obstacles. Epilipids are characterized by low abundance, high structural diversity, high number of isomers/isobars, and display specific fragmentation pattern differing from their unmodified counterparts. Even their annotation is not always univocally defined due to the complexity of the epilipidome. Therefore, software and computational approaches suitable for epilipidomics are highly required to facilitate the analysis of the acquired analytical data, and the number of in silico tools for this purposed is rapidly growing. Here, we review software, in silico approaches and databases currently available for LC-MS-based epilipidomics. The general workflow of an epilipidomics analysis by LC-MS will be briefly described to highlight the specific challenges that computational tools are expected to address. Thus, currently available computational tools for epilipidomics data processing, lipid identification, lipid quantification and data visualization will be described into detail. Finally, a list of databases including epilipids that might find wide application will be reviewed and proposals for future implementations of software will be provided.
2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1543473
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