Lipidomic Analysis
Lipidomic Analysis - Related Videos
06:48
On-Site Sampling and Extraction of Brain Tumors for Metabolomics and Lipidomics Analysis
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Cited by 13 •
2020
The manuscript presents on-site sampling of human brain tumors with solid phase microextraction followed by their biochemical profiling towards the discovery of biomarkers.
08:16
Phenol Red Thread-based Sampling Procedure for Untargeted Tear Fluid Lipidomics in Biomarker Discovery
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2025
This protocol describes a unique clinical protocol for collecting human tear fluid samples using phenol red threads and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based workflow to discover the tear lipidomic profile. The simple methyl tert-butyl ether (MTBE)/methanol biphasic separation method enables rapid tear lipid extraction with high recovery for tear biomarker discovery.
11:46
Shotgun Lipidomics of Rodent Tissues
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Cited by 1 •
2022
Shotgun mass spectrometry-based lipidomics delivers a sensitive quantitative snapshot of a broad spectrum of lipid classes simultaneously in a single measurement from various rodent tissues.
09:58
Lipidomics and Transcriptomics in Neurological Diseases
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Cited by 13 •
2022
This article presents a modular protocol for tissue lipidomics and transcriptomics, and plasma lipidomics in neurological disease mouse models targeting lipids underlying inflammation and neuronal activity, membrane lipids, downstream messengers, and mRNA-encoding enzymes/receptors underlying lipid function. Sampling, sample processing, extraction, and quantification procedures are outlined.
08:56
Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry
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Cited by 3 •
2020
We present a protocol using liquid chromatography coupled with tandem mass spectrometry to identify and quantify major cellular lipids in Saccharomyces cerevisiae. The described method for a quantitative assessment of major lipid classes within a yeast cell is versatile, robust, and sensitive.
FAQs
Chromatographic separation first resolves lipids according to their chemical properties, while mass spectrometry measures mass-to-charge ratios to distinguish the separated species. Used together, these stages support both qualitative identification and quantitative profiling rather than treating the sample as a single undifferentiated lipid mixture. This combination also helps detect structural changes relevant to immune activation or infection.
Structural changes may reveal biological shifts that lipid identity or abundance alone would not capture. Examining altered membrane lipids, inflammatory mediators, and pathogen-derived lipids can connect a profile to immune activation, infection, or host–pathogen interactions. This perspective helps researchers investigate metabolic pathways rather than only recording whether overall lipid abundance has increased or decreased.
Pathogen-derived lipids can provide molecular evidence of the pathogen’s contribution to the lipid profile during infection. Examining these components alongside host membrane lipids and inflammatory mediators helps researchers study host–pathogen interactions and distinguish changes associated with the infecting organism from changes linked to the host immune response. Such information can clarify infection-related metabolic pathways.
A typical workflow begins by extracting lipids from a biological sample. The extract then undergoes chromatographic separation, followed by mass spectrometric measurement. Chromatography separates components according to chemical properties, and mass spectrometry distinguishes lipid species through their mass-to-charge ratios. The resulting measurements support qualitative and quantitative profiling of lipid identities, abundances, and structural changes.
Researchers can apply the method when they need to track lipid changes during immune activation or infection. Profiles may include membrane lipids, inflammatory mediators, and pathogen-derived lipids, allowing investigators to examine how host and pathogen biology interact. These measurements can help clarify disease-associated metabolism, identify potential biomarkers, and reveal pathways relevant to therapeutic development.
Lipid profiles can expose patterns associated with health, disease, immune activation, or infection. Researchers may use these patterns to identify biomarkers that distinguish biologically meaningful states or to locate metabolic pathways altered during host–pathogen interactions. Pathway-level information can then guide therapeutic development by indicating which lipid-related processes warrant further investigation.