Creative Proteomics provides comprehensive lipidomics services, including untargeted and targeted lipid analysis, MALDI-imaging, metabolic flux analysis, and bioinformatics, to support research in various fields such as biotechnology, disease research, food safety, and environmental toxicology.
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What is Lipidomics
Service We Provide
Instruments
Advantages
Data Analysis Reports
Applications
Sample Requirements
FAQ
What is Lipidomics?
Lipids are essential metabolites that have many crucial cellular functions and can provide a direct readout of cellular metabolic status. The total lipid content in a cell is called a lipidome. Lipidomics is the study of lipidomes using the principles and techniques of analytical chemistry, and emerged in 2003 as an approach to study the metabolism of the cellular lipidome. The analytical power of, and new developments in, mass spectrometry (MS) have accelerated this emerging discipline.
Lipidomics enables us to study cellular metabolism by quantifying the changes of individual lipid classes, subclasses and molecular species that reflect metabolic differences. As the pathways and networks of lipid metabolism have been extensively studied, any changes in lipid amounts can simultaneously reveal variations in several enzymatic levels, activities and/or gene expression patterns.
Creative Proteomics has extensive experience in the field of lipidomics. We are dedicated to providing cutting-edge mass spectrometry (MS)-based lipidomics services for biomedical research institutions, biotechnology and pharmaceutical companies.
Lipidomics Service We Can Provide
Lipidomics services offer a comprehensive suite of solutions designed to analyze, quantify, and interpret lipid compositions in biological samples. These services help researchers explore lipid metabolic pathways, identify biomarkers, and understand the roles of lipids in various biological processes.
Targeted Lipidomics is designed to identify and quantify specific groups of lipids, focusing on known lipid classes and metabolic pathways. This method is highly precise, making it an ideal choice for validating biological hypotheses, studying defined metabolic networks, and identifying potential biomarkers.
Untargeted lipidomics focuses on discovering new lipid species and analyzing the lipidome in a comprehensive, unbiased manner. This approach is ideal for identifying known and novel lipids and understanding complex lipid profiles within biological systems. By capturing a wide range of lipids, it supports comparative studies across different experimental conditions, such as disease models, therapeutic interventions, and cellular responses.
Detection of Known and Unknown Lipids
This approach aims to identify both known lipids and unknown lipid species within a sample. It allows for the discovery of lipid species that may not have been previously recognized, enhancing the understanding of lipid biology in health and disease.
Comparative Lipid Profiling
Untargeted lipidomics enables researchers to compare lipid profiles across different experimental groups or conditions, helping to identify lipid-based biomarkers for diseases or therapeutic responses.
Biomarker Discovery
By identifying lipid changes linked to specific biological processes, researchers can discover potential biomarkers for disease diagnosis, prognosis, or treatment efficacy.
MALDI-Imaging Lipidomics (Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry) enables spatially resolved lipid profiling within tissue sections. By visualizing lipid distributions in situ, this technique allows for the study of lipid heterogeneity at the cellular and tissue levels. It is a powerful tool for understanding the spatial relationship of lipids in disease, development, and response to treatments.
Tissue-Specific Lipid Profiling:
Spatial Mapping of Lipids: MALDI-IMS allows researchers to visualize lipid distribution in tissue samples, providing critical information on the localization of specific lipids within different tissue types or cellular compartments.
Tissue Heterogeneity: This method helps identify tissue-specific lipid composition, highlighting the differences in lipid profiles between healthy and diseased tissues, or across different disease states, such as cancer or neurodegeneration.
Targeted Tissue Imaging: Researchers can study specific tissue regions of interest by customizing imaging protocols to focus on areas of interest, such as tumor boundaries, inflammatory regions, or drug-treated tissues.
High Sensitivity and Resolution:
Detailed Lipid Characterization: MALDI-IMS provides high sensitivity and resolution, enabling the detection of low-abundance lipids and fine-scale lipid variations in tissues. This is essential for detailed studies of lipid-related biological processes, such as lipid signaling in neural, cardiovascular, or metabolic diseases.
Simultaneous Lipid and Protein Imaging: In combination with tissue protein analysis, MALDI-IMS can provide a multi-dimensional understanding of lipid-protein interactions and their roles in cellular pathways.
Metabolic Flux Analysis (MFA) in lipidomics tracks the metabolic pathways of lipids by measuring the flow of metabolites through different biochemical pathways. This helps to elucidate how lipids are synthesized, modified, and degraded in various cellular processes. MFA can be applied in both targeted and untargeted modes, offering insights into lipid metabolism under normal and altered conditions, such as disease, stress, or treatment exposure.
Lipids Metabolism Analysis:
Targeted and Untargeted MFA: Both targeted and untargeted methods are used to trace the movement of lipid metabolites, enabling researchers to measure the production, consumption, and turnover of lipids in living systems.
Pathway Mapping: MFA helps map lipid biosynthesis and catabolism pathways, providing insights into the enzymes and metabolic intermediates involved. It is particularly useful in understanding lipid metabolism in diseases like cancer, metabolic disorders, and cardiovascular diseases.
Dynamic Flux Profiling: MFA allows researchers to capture dynamic changes in lipid flux under different conditions, revealing how metabolic flux is regulated in response to environmental factors, stress, or disease states.
Regulation of Lipid Metabolism:
Tracking Lipid Modifications: MFA can track modifications such as lipid oxidation, phosphorylation, or conjugation, which are critical for lipid function in signaling, membrane integrity, and energy storage.
Insights into Enzyme Activity: By quantifying flux through various metabolic pathways, MFA provides insights into the activity of key metabolic enzymes and how they are regulated in response to cellular cues or external treatments.
Lipidomics bioinformatic analysis integrates complex lipidomics data into meaningful biological insights. This service involves the use of advanced software tools to process, analyze, and interpret lipidomic data. By utilizing state-of-the-art bioinformatic methods, researchers can extract statistically significant patterns, perform comparative analysis, and visualize lipid data in intuitive ways.
Data Analysis and Reporting:
Comprehensive Statistical Analysis: Using tools like Progenesis QI, LipidSearch, and MS DIAL, researchers can perform in-depth statistical analysis of lipidomics data. This includes data normalization, differential analysis, and pathway enrichment to uncover lipid-specific biological insights.
Integration with Biological Context: Lipidomics data is analyzed in the context of biological systems, helping researchers understand lipid metabolism, lipid signaling, and lipid-protein interactions.
Customized Reporting: Detailed reports are generated, including experimental details, data visualizations (e.g., heatmaps, volcano plots), and figures ready for publication. These reports help researchers communicate their findings to the scientific community.
Visualization and Interpretation:
Data Visualizations: High-quality visualizations, including lipidomic profiles, PCA (Principal Component Analysis), and volcano plots, help researchers interpret complex lipidomics data easily and make data-driven decisions.
Pathway Mapping and Biomarker Discovery: Bioinformatic tools can also be used to map lipid metabolic pathways and identify potential biomarkers for diseases or therapeutic interventions.
Comparative Lipidomics Analysis:
Cross-Sample Comparison: This service enables the comparison of lipid profiles across different experimental groups, such as control versus treated samples, allowing for the identification of lipid alterations associated with diseases or treatments.
What Instruments are Used in Lipidomics?
Lipidomics requires a variety of high-performance instruments for the detailed analysis of lipids, each tailored to specific aspects of lipid characterization, quantification, and profiling.
Mass Spectrometers (MS)
Triple Quadrupole MS (QqQ): Instruments like the SCIEX Triple Quad 6500+ and SCIEX 7500 systems are widely used for targeted lipidomics. They offer high sensitivity and selectivity through multiple reaction monitoring (MRM), making them ideal for accurate lipid quantification.
Time-of-Flight MS (TOF): The ZenoTOF 7600 system is a high-resolution mass spectrometer that uses Electron Activated Dissociation (EAD) technology. This system is particularly useful for untargeted lipidomics, offering comprehensive lipid profiling and the ability to elucidate lipid structures in a single experiment.
Orbitrap MS: Orbitrap mass spectrometers, like the Thermo Fisher Q Exactive, provide high-resolution and accurate mass capabilities. These systems are ideal for detailed lipidomic studies, offering precision in both targeted and untargeted lipid analysis.
SCIEX Triple Quad 6500+ (Figure from SCIEX)
ZenoTOF 7600 system (Figure from SCIEX)
Thermo Fisher Q Exactive (Figure from Thermo Fisher)
Differential Ion Mobility Spectrometry (DIMS)
The SelexION device enhances the performance of mass spectrometers by allowing the separation of lipid isomers and isobars in the gas phase. It improves selectivity and accuracy, especially when integrated with HPLC or UHPLC systems, which can further separate lipids before MS analysis.
Liquid Chromatography (LC)
High-Performance Liquid Chromatography (HPLC) and Ultra-High-Performance Liquid Chromatography (UHPLC) are frequently used in lipidomics alongside mass spectrometry. These chromatography techniques separate lipids based on their size, polarity, or chemical properties, providing improved resolution and cleaner data for complex lipid mixtures.
Gas Chromatography (GC)
GC-Flame Ionization Detection (GC-FID) is useful for analyzing volatile or derivatized lipid species, such as fatty acids. While GC-FID offers high sensitivity, it is more commonly used for profiling fatty acid composition than for broad lipidomic analysis, as non-volatile lipids often require derivatization for effective analysis.
GC-MS: Gas chromatography coupled with mass spectrometry (GC-MS) is a powerful tool for identifying and quantifying lipid species, particularly fatty acids and their derivatives. This combination offers both detailed structural information and high sensitivity for lipid analysis.
Why Choose Our Lipidomics Services?
Comprehensive analysis of over 100 lipid classes and 4,000+ individual lipid species.
Compatible with diverse sample types, including cells, tissues, body fluids, and more.
Ultra-sensitive detection down to the picogram level using advanced instruments.
Requires minimal sample amounts, such as 1 µL of blood plasma.
High-throughput capability, processing thousands of samples weekly.
Accurate lipid identification using robust annotation techniques and curated databases.
Fast turnaround time with results delivered in as little as two weeks.
Covers more than 1.7 million lipid molecules with advanced MS2 & MS3 data.
Stringent quality control with 9 key checkpoints to ensure reliable results.
Tailored project design to meet specific research needs and sample requirements.
Expert lipid extraction and preparation guidance provided.
Access to a comprehensive lipid database with 8 major categories and 300 subclasses.
Semi-quantitative analysis supported by 14 isotope-labeled lipid standards.
Lipidome Data Analysis Workflow and Reports
Workflow of Lipidome Data Analysis
Overview Report-Initial Insights
This report provides a foundational overview of the lipidomics data, summarizing key metrics to ensure the quality of data for further exploration.
Key Features:
Breakdown of lipid classes and categories across all samples.
Summary of sample preparation quality and total lipid content.
Visual representations such as bar charts and PCA plots for a quick overview.
The goal of this report is to offer a high-level snapshot of lipidomic profiles and verify the reliability of the analysis process, setting the stage for deeper investigations.
Figure from Sveeggen, Timothy. Diss. 2022
Analytical Report-Detailed Exploration
Designed for more advanced analysis, this report dives deeper into lipidomics data, helping researchers identify patterns and trends within their datasets.
Key Features:
Sub-class lipid profiling, including chain length, double bonds, and hydroxylation patterns.
Comparative analysis to identify lipid changes across different conditions or treatments.
Statistical testing (e.g., ANOVA) to detect significant lipid alterations.
Access to visualization tools for creating custom graphs and exporting tailored data views.
This report helps to better understand lipid dynamics and supports the formulation of new hypotheses for further research.
Statistical and Customized Report-Targeted Insights
This specialized report offers in-depth statistical analyses and customized data interpretation to address specific research questions.
Key Features:
Correlation analyses of lipid classes and sub-species.
Cohort comparisons to analyze differences between experimental groups.
Pathway enrichment and feature-specific analysis to identify significant biological trends.
Tailored statistical methods for biomarker discovery and validation.
Designed to provide high-value insights, this report is tailored to meet the specific experimental needs of researchers.
Explore our Lipidomics Solutions brochure to learn more about our comprehensive lipidomics analysis platform.
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.
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.
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.
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.
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.
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.
Sample Requirements for Lipidomics Solutions
Sample Type
Recommended Sample Amount
Minimum Sample Amount
Serum/Plasma
≥ 300 µL
≥ 100 µL
Urine
≥ 300 µL
≥ 100 µL
Animal Tissue
≥ 100 mg
≥ 25 mg
Plant Tissue
≥ 1 g
≥ 100 mg
Feces/Intestinal Contents
≥ 200 mg
≥ 25 mg
Cells
≥ 1 × 10⁷
≥ 5 × 10⁶
Microorganisms
≥ 200 mg
≥ 25 mg
Culture Medium/Fermentation Medium
≥ 1 mL
≥ 100 µL
Milk
≥ 1 mL
≥ 100 µL
Other Body Fluids (Amniotic Fluid, Saliva, Hemolymph, Cerebrospinal Fluid, etc.)
≥ 300 µL
≥ 100 µL
Swab
2 samples
2 samples
Soil Sample
≥ 1 g
≥ 1 g
Frequently Asked Questions for Lipidomics Service
How do I choose between different lipid extraction methods for my samples?
The choice of lipid extraction method largely depends on the sample type and the goal of your lipidomics study.
Bligh and Dyer Method (BDC): A widely used method for extracting total lipids from biological samples like tissues and plasma. It's effective for a broad range of lipid classes.
Folch Method: Another popular method, particularly for isolating phospholipids and cholesterol from tissues. However, it may not be as effective for certain polar lipids, such as sphingolipids.
Solid-Phase Extraction (SPE): This method is often used for fractionating lipids based on polarity, which can be helpful when you want to focus on specific lipid classes (e.g., phospholipids or triglycerides).
Hexane-Isopropanol Extraction: Effective for separating neutral lipids, such as triglycerides and fatty acids.
What is the best way to preserve samples before lipid extraction?
Lipid degradation can occur quickly after sample collection, especially with biological samples. To preserve the integrity of lipids before extraction:
Freeze Samples Immediately: For most biological samples (e.g., blood, tissues), it is crucial to freeze them at -80°C or in liquid nitrogen immediately after collection to prevent lipid degradation.
Avoid Repeated Freeze-Thaw Cycles: Repeated freezing and thawing can cause lipid degradation and variability in results. Store samples in aliquots to avoid multiple freeze-thaw cycles.
Use Stabilizing Agents: In some cases, adding stabilizing agents such as antioxidants (e.g., ascorbic acid) to the samples can help preserve lipid integrity, especially for volatile lipids or lipids prone to oxidation.
What are the common pitfalls during lipid extraction, and how can I avoid them?
Lipid extraction is a delicate process, and errors at this stage can affect the quality of the results. Common pitfalls include:
Incomplete Lipid Extraction: Incomplete extraction can occur if the wrong solvent or extraction procedure is used. It's essential to ensure that the protocol is suited to the sample type and lipid class being studied.
Contamination with Polar or Non-Lipid Components: Non-lipid components, like proteins or metabolites, can interfere with lipidomics analysis. Proper phase separation and sample cleanup are necessary to avoid contamination.
Degradation of Labile Lipids: Some lipid classes, such as polyunsaturated fatty acids and oxylipins, are highly susceptible to degradation during extraction. Using antioxidants and minimizing sample handling time can help mitigate this issue.
How can I ensure consistent sampling across experimental groups?
Consistency in sampling is crucial for minimizing variability and obtaining reliable results.
Standardize Sample Collection Protocols: Ensure that all samples are collected under the same conditions (e.g., time of day, temperature, handling) to minimize biological variability.
Sample Handling: Always use clean, sterile equipment, and avoid contamination from external sources. For liquid samples like plasma or serum, ensure rapid separation and storage at appropriate temperatures.
Avoid Delays in Processing: The sooner samples are processed or frozen after collection, the better. Delays can lead to lipid degradation or changes in lipid composition due to enzymatic activities.
If your study involves multiple sampling time points or experimental groups, it's important to develop a clear sampling protocol to ensure consistency across all conditions.
Can you help me with the proper storage and handling of tissue samples for lipidomics analysis?
Yes, proper storage and handling of tissue samples are critical to maintaining lipid integrity.
Immediately Flash-Freezing: After dissection, tissues should be flash-frozen in liquid nitrogen and stored at -80°C to prevent lipid degradation.
Avoiding Autolysis: Enzymatic activity can break down lipids if tissues are not rapidly frozen. Ensure that tissues are immediately frozen in cryovials or on dry ice.
Sample Homogenization: When preparing tissue samples, it's important to homogenize them thoroughly to ensure even extraction of lipids. Mechanical homogenization (e.g., bead mills or tissue grinders) is commonly used for this purpose.
We can provide customized protocols for handling various tissue types and offer advice on optimizing storage conditions for different lipid classes.
Annexin A2 modulates phospholipid membrane composition upstream of Arp2 to control angiogenic sprout initiation. The FASEB Journal, 2023. https://doi.org/10.1096/fj.202201088R
Multi‐omics identify xanthine as a pro‐survival metabolite for nematodes with mitochondrial dysfunction. EMBO Journal, 2019. https://doi.org/10.15252/embj.201899558
* Our services can only be used for research purposes and Not for clinical use.
Workflow of Lipidome Data Analysis
