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Authors = Gerald N. Rechberger

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Open AccessReview Mass Spectrometry Based Lipidomics: An Overview of Technological Platforms
Metabolites 2012, 2(1), 19-38; doi:10.3390/metabo2010019
Received: 23 November 2011 / Revised: 22 December 2011 / Accepted: 24 December 2011 / Published: 5 January 2012
Cited by 42 | Viewed by 3621 | PDF Full-text (411 KB) | HTML Full-text | XML Full-text
Abstract
One decade after the genomic and the proteomic life science revolution, new ‘omics’ fields are emerging. The metabolome encompasses the entity of small molecules—Most often end products of a catalytic process regulated by genes and proteins—with the lipidome being its fat soluble subdivision.
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One decade after the genomic and the proteomic life science revolution, new ‘omics’ fields are emerging. The metabolome encompasses the entity of small molecules—Most often end products of a catalytic process regulated by genes and proteins—with the lipidome being its fat soluble subdivision. Within recent years, lipids are more and more regarded not only as energy storage compounds but also as interactive players in various cellular regulation cycles and thus attain rising interest in the bio-medical community. The field of lipidomics is, on one hand, fuelled by analytical technology advances, particularly mass spectrometry and chromatography, but on the other hand new biological questions also drive analytical technology developments. Compared to fairly standardized genomic or proteomic high-throughput protocols, the high degree of molecular heterogeneity adds a special analytical challenge to lipidomic analysis. In this review, we will take a closer look at various mass spectrometric platforms for lipidomic analysis. We will focus on the advantages and limitations of various experimental setups like ‘shotgun lipidomics’, liquid chromatography—Mass spectrometry (LC-MS) and matrix assisted laser desorption ionization-time of flight (MALDI-TOF) based approaches. We will also examine available software packages for data analysis, which nowadays is in fact the rate limiting step for most ‘omics’ workflows. Full article
(This article belongs to the Special Issue Lipidomics)

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