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Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis

Lipidomics is the comprehensive analysis of lipids in a given biological system. This investigation is often limited by the low amount and high complexity of biological samples, therefore highly sensitive lipidomics methods are required. Nanoflow-LC/MS offers extremely high sensitivity; however, it...

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Autores principales: Cattaneo, Angela, Martano, Giuseppe, Restuccia, Umberto, Tronci, Laura, Bianchi, Michele, Bachi, Angela, Matafora, Vittoria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8623082/
https://www.ncbi.nlm.nih.gov/pubmed/34822378
http://dx.doi.org/10.3390/metabo11110720
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author Cattaneo, Angela
Martano, Giuseppe
Restuccia, Umberto
Tronci, Laura
Bianchi, Michele
Bachi, Angela
Matafora, Vittoria
author_facet Cattaneo, Angela
Martano, Giuseppe
Restuccia, Umberto
Tronci, Laura
Bianchi, Michele
Bachi, Angela
Matafora, Vittoria
author_sort Cattaneo, Angela
collection PubMed
description Lipidomics is the comprehensive analysis of lipids in a given biological system. This investigation is often limited by the low amount and high complexity of biological samples, therefore highly sensitive lipidomics methods are required. Nanoflow-LC/MS offers extremely high sensitivity; however, it is challenging as a more demanding maintenance is often needed compared to conventional microflow-LC approaches. Here, we developed a sensitive and reproducible lipidomics LC method, termed Opti-nQL, which can be applied to any biological system. Opti-nQL has been validated with cellular lipid extracts of human and mouse origin and with different lipid extraction methods. Among the resulting 4000 detected features, 700 and even more unique lipid molecular species have been identified covering 16 lipid sub-classes, while 400 lipids were uniquely structure defined by MS/MS. These results were obtained by analyzing an amount of lipids extract equivalent to 40 ng of proteins, being highly suitable for low abundant samples. MS analysis showed that theOpti-nQL method increases the number of identified lipids, which is evidenced by injecting 20 times less material than in microflow based chromatography, being more reproducible and accurate thus enhancing robustness of lipidomics analysis.
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spelling pubmed-86230822021-11-27 Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis Cattaneo, Angela Martano, Giuseppe Restuccia, Umberto Tronci, Laura Bianchi, Michele Bachi, Angela Matafora, Vittoria Metabolites Article Lipidomics is the comprehensive analysis of lipids in a given biological system. This investigation is often limited by the low amount and high complexity of biological samples, therefore highly sensitive lipidomics methods are required. Nanoflow-LC/MS offers extremely high sensitivity; however, it is challenging as a more demanding maintenance is often needed compared to conventional microflow-LC approaches. Here, we developed a sensitive and reproducible lipidomics LC method, termed Opti-nQL, which can be applied to any biological system. Opti-nQL has been validated with cellular lipid extracts of human and mouse origin and with different lipid extraction methods. Among the resulting 4000 detected features, 700 and even more unique lipid molecular species have been identified covering 16 lipid sub-classes, while 400 lipids were uniquely structure defined by MS/MS. These results were obtained by analyzing an amount of lipids extract equivalent to 40 ng of proteins, being highly suitable for low abundant samples. MS analysis showed that theOpti-nQL method increases the number of identified lipids, which is evidenced by injecting 20 times less material than in microflow based chromatography, being more reproducible and accurate thus enhancing robustness of lipidomics analysis. MDPI 2021-10-21 /pmc/articles/PMC8623082/ /pubmed/34822378 http://dx.doi.org/10.3390/metabo11110720 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cattaneo, Angela
Martano, Giuseppe
Restuccia, Umberto
Tronci, Laura
Bianchi, Michele
Bachi, Angela
Matafora, Vittoria
Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis
title Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis
title_full Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis
title_fullStr Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis
title_full_unstemmed Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis
title_short Opti-nQL: An Optimized, Versatile and Sensitive Nano-LC Method for MS-Based Lipidomics Analysis
title_sort opti-nql: an optimized, versatile and sensitive nano-lc method for ms-based lipidomics analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8623082/
https://www.ncbi.nlm.nih.gov/pubmed/34822378
http://dx.doi.org/10.3390/metabo11110720
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