Targeted Lipidomics Service

Creative Proteomics offers targeted lipidomics services for accurate lipid quantification and biomarker discovery. We use advanced LC-MS/MS and GC-MS platforms to analyze thousands of lipid species. Our services support disease research, drug development, and metabolic studies with reliable and reproducible data.

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What is Targeted Lipidomics?

Targeted Lipidomics is a specialized analytical approach that focuses on the precise quantification of specific lipid species. Unlike untargeted lipidomics, which provides broad lipid profiling, targeted lipidomics is designed to deliver accurate, reproducible data on lipid concentrations using established internal standards and multiple reaction monitoring (MRM) methods.

This technique is widely used in research areas that require quantitative lipid measurements to investigate lipid-related metabolic pathways, monitor physiological changes, and explore the role of lipids in various biological processes.

Targeted Lipidomics Service in Creative Proteomics

At Creative Proteomics, we offer specialized targeted lipidomics services for precise lipid quantification, structural characterization, and metabolic analysis, supporting diverse research applications.

Comprehensive Lipid Quantification

Utilizing LC-MS/MS with MRM mode, we deliver precise quantification of 8 major lipid classes and 50+ subclasses. Dynamic range: 4–6 orders of magnitude, enabling detection of trace to abundant lipids in cells, tissues, and biofluids.

Disease-Focused Lipid Panels

Preconfigured panels for cardiometabolic disorders, neuroinflammation, and cancer biomarkers, such as oxidized LDL, pro-apoptotic ceramides (C16:0/C18:0), and lysophosphatidic acid (LPA). Sensitivity as low as 0.1 pmol/mL, ideal for mechanistic studies and preclinical validation.

Structural Characterization of Modified Lipids

High-resolution Q-TOF and LIPID MAPS® database integration enable identification of oxidized lipids (e.g., 4-HNE), acetylated/glycosylated phospholipids, and branched-chain fatty acids, elucidating roles in oxidative stress and signaling pathways.

Lipid Metabolic Flux Analysis

13C/2H isotope tracing tracks lipid turnover in pathways like mitochondrial β-oxidation and phospholipid remodeling. Kinetic modeling quantifies flux rates, supporting research on metabolic diseases and drug mechanisms.

Custom Lipidomics Solutions

Tailored assays for novel lipids or complex matrices (e.g., extracellular vesicles, plant cuticular waxes). Optimized protocols for challenging samples (FFPE tissues, microbial biofilms), validated via spike-recovery and precision tests (CV <15%).

Advanced Data Analysis

Deliverables include interactive pathway maps, machine learning-powered biomarker heatmaps, and PCA plots. Compatible with MetaboAnalyst 5.0 and GraphPad Prism for streamlined analysis and publication-ready visuals.

List of Detected Lipidomics Panel

  • Fatty Acyls
  • Glycerophospholipids
  • Sphingolipids
  • Sterol Lipids
  • Glycerolipids
  • Prenol Lipids
  • Saccharolipids
  • Polyketides

Fatty Acyls Anlysis

Fatty acyls refer to the fatty acid derivatives and their oxidized products. These include various signaling lipids.

Glycerophospholipids Analysis

These lipids form a major component of cell membranes and are involved in signaling pathways.

Sphingolipids Analysis

Sterol Lipids Analysis

Glycerolipids Analysis

Prenol Lipids

  • Isoprenoids: Farnesol, Geranylgeraniol
  • Polyprenols: Dolichols
  • Epoxysqualene
  • Coenzyme Q10
  • Phytol

Saccharolipids

  • Lipopolysaccharides (LPS): Lipid A
  • Glycolipids: Rhamnolipids, Glucosylceramides
  • Sophorolipids

Polyketides

  • Macrolides: Erythromycin
  • Tetracyclines: Doxycycline
  • Polyphenols: Curcumin, Resveratrol
  • Avermectins: Ivermectin

Why Choose Our Targeted Lipidomics Services?

  • High Sensitivity and Accuracy – Detection limits as low as 1 pmol with LC-MS/MS and GC-MS.
  • Comprehensive Lipid Coverage: Simultaneous detection of 2,400+ lipid species across 8 major classes (e.g., glycerophospholipids, sphingolipids, sterols) and 50+ subclasses.
  • Efficient Turnaround Time: With optimized workflows, we deliver reliable results within 2-4 weeks.
  • Flexible Sample Types: Compatible with a wide range of biological materials, including plasma, serum, tissues, and cell lysates.
  • High Sensitivity and Accuracy: Achieve sub-ppm mass accuracy and detect lipids at trace levels with a lower limit of quantification (LLOQ) of 1 pmol, ensuring reliable results for low-abundance lipids.
  • Absolute Quantification: Ensure precise and reproducible results with stable isotope-labeled standards used for internal calibration and normalization. Dual chromatography separation (C18 and HILIC columns) reduces cross-talk between lipid classes and improves resolution.
  • Exceptional Reproducibility: Maintain data consistency with coefficient of variation (CV) values below 10%, ensuring high reproducibility across samples and batches
  • Robust Quality Control: Automated sample preparation systems and QC samples (e.g., pooled biological replicates) monitor batch-to-batch consistency.
  • Tailored Data Analysis: Advanced bioinformatics pipelines for pathway enrichment, trend clustering, and machine learning-based biomarker discovery.

How Creative Proteomics Provides Targeted Lipidomics Analysis

Workflow for Targeted Lipidomics

What Platforms are Used for Our Targeted Lipidomics Analysis?

AB SCIEX 6500+ QTRAP

AB SCIEX 6500+ QTRAP (Figure from SCIEX)

Thermo Scientific™ UltiMate™ 3000

Thermo Scientific™ UltiMate™ 3000 (Figure from Thermo Fisher)

Agilent 7890A GC System

Agilent 7890A GC System (Figure from Agilent)

Targeted Lipidomics Analysis Service: Results and Data Analysis

Comprehensive Overview Report

This report delivers a high-level summary of lipidomic data, ensuring data quality and offering an initial understanding of lipid distribution across samples.

Key Features:

  • Overview of lipid classes and subclasses with clear visual representation.
  • Quality control assessment with internal standard performance evaluation.
  • Total lipid content comparison across experimental groups.
  • Principal Component Analysis (PCA) for clustering and variance evaluation.

This report acts as a preliminary checkpoint, ensuring robust data for further exploration.

Chromatogram of diacylglycerol (DAG) and ceramide (CER) standard mixture. An overlay of multiple reaction monitoring (MRM) chromatograms of individual lipid species is shown.

Chromatogram of diacylglycerol (DAG) and ceramide (CER) standard mixture (Preuss, Christina, et al. 2019).

In-Depth Analytical Report

Dive deeper into your lipidomics data with detailed profiling, comparative analysis, and identification of lipid variations.

Key Features:

  • Comprehensive lipid species quantification across different conditions.
  • Statistical analysis (e.g., t-tests, ANOVA) to identify significant changes.
  • Structural characterization based on chain length, saturation, and hydroxylation.
  • Heatmaps, volcano plots, and correlation matrices for visual insights.

This analysis aids in identifying lipid biomarkers and understanding biological responses.

Customized Statistical and Pathway Analysis Report

Designed for hypothesis-driven research, this report provides tailored insights through statistical modeling and pathway enrichment analysis.

Key Features:

  • Targeted comparisons of lipid profiles across experimental or clinical cohorts.
  • Correlation and regression analysis for biomarker identification.
  • Pathway enrichment to uncover metabolic pathways linked to lipid alterations.
  • Data visualization for presenting key findings in publications or presentations.

Explore our Lipidomics Solutions brochure to learn more about our comprehensive lipidomics analysis platform.

Download Brochure

Sample Requirements for Targeted Lipidomics Solutions

Sample TypeSample CollectionLysis MethodRecommended QuantityAdditional Considerations
TissuesHomogenization for cell releaseTissue-specific lysis protocols10-50 mg tissueTissue-specific considerations; avoid contamination during handling.
Cell CultureHarvesting with trypsin or other methodsSpecialized buffers for efficient lysisVaries based on culture dishConsistent culture conditions and avoiding contamination are crucial.
Plasma/SerumBlood collection with anticoagulantsProtein precipitation or organic extraction100-500 μLImmediate sample processing to prevent lipid alterations.
Cell PelletsCentrifugation and washingSpecialized detergents for efficient lysis1-5 x 10^6 cellsOptimize washing steps to minimize cell residue.
LipoproteinsUltracentrifugation or density gradientOrganic extraction or specialized methods50-200 μLHandle lipoproteins with care to prevent structural alterations.
ExosomesUltracentrifugation or precipitationSpecialized extraction methods100-500 μLMaintain proper exosome isolation techniques for accurate analysis.
Breast MilkCollection in clean containersLipid extraction from milk5-10 mLMinimize contamination during collection and processing.
Skin BiopsyBiopsy procedureTissue-specific lysis protocols5-10 mg tissuePreserve sample integrity and prevent degradation.
UrineMidstream collection in sterile containersOrganic extraction or precipitation5-10 mLProcess samples promptly to prevent lipid changes.
FecesFresh collection in airtight containersHomogenization and organic extraction100-500 mgMinimize oxygen exposure to maintain sample stability.
PlantsHarvest and flash freezeTissue-specific lysis protocols50-200 mgRapid freezing preserves lipid profiles in plant tissues.
MicroorganismsCulture or direct collectionCell lysis and extraction methodsVaries based on biomassChoose appropriate lysis methods for different microorganisms.
FoodHomogenization or extractionSolvent-based extraction methodsVaries based on food typeTailor extraction methods to the characteristics of the food sample.

What Our Targeted Lipidomics Analysis Used For

Pharma & Biotech

In the pharmaceutical and biotechnology fields, lipidomics is used to identify lipid-based biomarkers, study the effects of drugs, and understand the underlying mechanisms of diseases. By analyzing how lipids change in response to treatments, researchers can improve drug development and discover new therapeutic targets.

Food & Nutrition

Lipidomics is vital in food science, helping to analyze the lipid content of different foods and their effects on health. It provides valuable insights into how dietary fats impact metabolic processes, inflammation, and the risk of chronic diseases like obesity and heart disease.

Disease Research

Lipidomics is increasingly used in disease research to explore how lipids contribute to conditions like cancer, cardiovascular diseases, neurodegeneration, and metabolic disorders. By examining lipid profiles in blood, tissues, and cells, researchers can identify new biomarkers and potential treatments.

Environmental Toxicology

In environmental toxicology, lipidomics helps assess how environmental pollutants affect lipid metabolism in animals, plants, and humans. It provides insights into how exposure to chemicals like pesticides or industrial toxins can alter lipid profiles, helping to identify potential health risks and environmental hazards.

Agriculture

Lipidomics can be applied to agriculture to study how plants and animals use lipids for growth, energy storage, and stress response. It helps improve crop quality, enhance resistance to diseases, and optimize animal health, supporting better agricultural practices and food production.

Microorganism

In microbiology, lipidomics is used to analyze the lipid profiles of bacteria, fungi, and other microorganisms. This research helps understand how microorganisms adapt to different environments, resist stress, or cause infections, and can lead to new ways of combating antibiotic resistance or improving industrial fermentation processes.

FAQs for Targeted Lipidomics Analysis Service

How should biological and technical replicates be designed for lipidomics studies? Are there specific recommendations?

  • Biological Replicates: At least 5 samples per group for clinical studies or 3 independent culture experiments for cell-based studies to account for individual variability.
  • Technical Replicates: 3 parallel injections per sample (from a single extraction) to assess instrument precision (CV typically <5%).
  • Low-Availability Samples: Use pooled QC samples (mixed from all samples) across batches to monitor data drift.

What are the critical steps for sample transportation and storage to prevent lipid degradation?

  • Blood/Biofluids:

Use EDTA plasma (not serum) to minimize platelet phospholipid interference. Centrifuge within 30 minutes at 4°C (2,000×g, 10 min), aliquot, and flash-freeze at -80°C. Ship on dry ice using frost-free tubes to avoid freeze-thaw cycles.

  • Tissues:

Rinse fresh tissues with ice-cold PBS before snap-freezing in liquid nitrogen. For FFPE samples, specify section thickness (5 μm) and fixation time (<48 hours).

How do you normalize lipidomics data from cell samples with varying viability or density?

  • Normalization Methods:

Use cell counts (trypan blue exclusion) or total protein quantification (BCA assay) as a baseline. For apoptotic cells (>20% apoptosis), apply FACS sorting to remove dead cells or use SPE purification to eliminate lyso-phospholipids.

  • Low-Cell Density: Concentrate samples to 1×10^6 cells/mL or use low-volume chromatography columns (e.g., 2.1 mm C18 columns).

How are internal standards (IS) selected and validated? Do they cover all target lipids?

  • Selection Criteria:
    • Structural analogs (e.g., d7-cholesteryl ester for CE, C17-sphingomyelin for SM).
    • Validated in blank matrices to confirm no endogenous interference.
  • Coverage Strategy:
    • For lipids without commercial IS (e.g., specific OxPLs), use isotope derivatization (e.g., D6-AA labeling) or class-specific IS (e.g., C16:0-Ceramide for all ceramide variants).

Can raw MS data (chromatograms, integration parameters) be provided for independent verification?

Yes. Deliverables include:

  • Raw MRM chromatograms (mzML format) with retention time, peak width (FWHM), and S/N ratios.
  • Integration Parameters: Baseline correction method (dynamic decay algorithm), peak height/area selection criteria.
  • Third-Party Compatibility: Data can be reanalyzed using Skyline, Progenesis QI, or similar tools.

How do you address low signal-to-noise ratios or missing peaks in the data?

We follow a 3-step troubleshooting protocol:

1. Retest: Freshly prepare mobile phases and reinject samples to rule out solvent degradation.

2. Matrix Enhancement: Add matrix-matched calibration curves for low-abundance lipids (e.g., lyso-PLs in serum).

3. Alternative Transitions: Re-optimize collision energy (CE) or validate secondary fragment ions (ion ratio consistency >70%).

What safeguards are in place to prevent lipid oxidation during sample preparation?

  • Chemical Protection:
    • Add 0.005% BHT/EDTA to lysis buffers to inhibit lipoxygenases.
    • Perform lipid extraction under nitrogen atmosphere to minimize PUFA oxidation.
  • Rapid Processing: Complete extraction within 30 minutes post-thawing; use cryogenic tissue grinding (e.g., Covaris cryoPREP).

How do you ensure accurate quantification across wide lipid concentration ranges (e.g., plasma TAG spanning 10^6)?

We employ a split dilution strategy:

  • High-Abundance Lipids (e.g., TAG): Analyze 1:100 diluted plasma with low-sensitivity MRM channels.
  • Low-Abundance Lipids (e.g., S1P): Use undiluted samples with high-sensitivity scans (Turbo V™ ion source).
  • Cross-Validation: Concentration differences between dilution conditions must be <20%.

Are species-specific lipid databases available for animal models (e.g., mice, zebrafish)?

Yes. Our curated databases include:

  • Mouse/Rat: ~12,000 lipids (aligned with Jackson Laboratory standards).
  • Zebrafish: Specialized for brain phospholipids (e.g., 22:6n3-PC) and yolk lipoproteins.
  • Non-Model Species (e.g., primates): Provide 5 blank samples to establish background exclusion lists.

Can you analyze lipid-protein or lipid-metabolite interactions as part of multi-omics studies?

We offer integrated cross-omics analysis:

  • Lipid-Protein: Co-regulation networks using STRING or Cytoscape (e.g., LDL receptor vs. plasma cholesterol esters).
  • Lipid-Metabolite: Pathway mapping via KEGG or Reactome (e.g., sphingolipid-ceramide interplay in apoptosis).

Publications

References

  1. Preuss, Christina, et al. "A new targeted lipidomics approach reveals lipid droplets in liver, muscle and heart as a repository for diacylglycerol and ceramide species in non-alcoholic fatty liver." Cells 8.3 (2019): 277.
  2. Naoe, Satoko, et al. "Characterization of lipid profiles after dietary intake of polyunsaturated fatty acids using integrated untargeted and targeted lipidomics." Metabolites 9.10 (2019): 241.
* Our services can only be used for research purposes and Not for clinical use.

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