Study on Lipid Fractions of Streptococcus thermophilus by TLC, GC and GC/MS Techniques

Pelizzola, Valeria; Povolo, Milena; Avalli, Andrea; Bottari, Benedetta; Neviani, Erasmo; Contarini, Giovanna

doi:10.2174/1874065000701010015

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…Using standards and yeast samples, it could be shown that lipid class-specific fractionation was successfully accomplished for 14 different lipid classes or subclasses (FA, DG, ST, MG, SPH, HexCer, PG, Hex2Cer, PC, SM, LPC, Cer d, Cer t, Cer e) paving the way to further purification, in-depth profiling, or facilitating a detailed fatty acyl chain composition determination via gas chromatography-mass spectrometry (GC-MS) as previously addressed by TLC or SPE [52,53]. Figure 3 gives a detailed overview of the fractionated lipid classes in yeast; the retention time of cholesterol, MG, Hex2Cer, AcCa, and SM was determined by the multi-lipid mix only.…”

Section: Resultsmentioning

confidence: 99%

Preparative supercritical fluid chromatography for lipid class fractionation—a novel strategy in high-resolution mass spectrometry based lipidomics

et al. 2020

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In this work, a lipidomics workflow based on offline semi-preparative lipid class-specific fractionation by supercritical fluid chromatography (SFC) followed by high-resolution mass spectrometry was introduced. The powerful SFC approach offered separation of a wide polarity range for lipids, enabled enrichment (up to 3 orders of magnitude) of lipids, selective fractionation of 14 lipid classes/ subclasses, and increased dynamic range enabling in-depth characterization. A significantly increased coverage of low abundant lipids improving lipid identification by numbers and degree (species and molecular level) was obtained in Pichia pastoris when comparing high-resolution mass spectrometry based lipidomics with and without prior fractionation. Proof-of-principle experiments using a standard reference material (SRM 1950, NIST) for human plasma showed that the proposed strategy enabled quantitative lipidomics. Indeed, for 70 lipids, the consensus values available for this sample could be met. Thus, the novel workflow is ideally suited for lipid class-specific purification/isolation from milligram amounts of sample while not compromising on omics type of analysis (identification and quantification). Finally, compared with established fractionation/pre-concentration approaches, semi-preparative SFC is superior in terms of versatility, as it involved only volatile modifiers and salt additives facilitating any follow-up use such as qualitative or quantitate analysis or further purification down to the single lipid species level.

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Section: Resultsmentioning

confidence: 99%