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Quantitative Lipidomics Data Analysis for Plants

Quantitative Lipidomics Data Analysis for Plants

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Lipids are a major component of cell membranes and an important source of energy and quality indicator. The resolution of lipid metabolism is of great importance in plant stress, development, food quality, and gene function characterization.

Introduction of Quantitative Lipidomics Data Analysis for Plants

The absolute quantification of lipidome based on mass spectrometry is a technique based on high-throughput analysis to systematically resolve the changes in lipid composition and content in organisms, reveal the alterations and functions of lipids in various biological processes, and then elucidate the related biological activity processes and mechanisms. Plant lipidomics is the analysis of lipids in plants using mass spectrometry. We typically use mass spectrometry to provide our customers with highly stable and reproducible quantitative analysis of plant lipids, followed by an iso-statistical analysis service of the raw data.

Flowchart of quantitative mass spectrometric analysis of lipid molecular species.Figure 1. Flowchart of quantitative mass spectrometric analysis of lipid molecular species. (Pranneshraj V, et al., 2022)

Project Workflow of Quantitative Lipidomics Data Analysis for Plants

Quantitative Lipidomics Data Analysis for Plants

Deliverables

We can provide the following analysis results, including but not limited to.

  • Results of diversified analysis of the lipidomics changes.
  • Heat map of metabolic changes in lipid subclasses.
  • Cluster analysis chart of lipid content trend.
  • Loop chart for lipid composition analysis.

How Can We Help You

Choosing our quantitative lipidomics data analysis for animals can help you solve the following problems.

  • The response of plants to biotic stress can be directly reflected in the processes of plant lipid anabolism and catabolism. Quantitative lipidomics analysis services can be applied in the study of the mechanisms of plant resistance to biotic stresses.
  • Membrane lipids can produce many substrates of signaling lipids, and the enzymatic production and metabolism of these signaling molecules are tightly regulated. Quantitative analysis of the lipidome can serve in the study of regulatory mechanisms in plants facing abiotic stresses.
  • Quantitative lipidomics analysis can be applied to the study of developmental processes in oilseed crops.

Can CD Genomics help me generate raw data?

Yes, we can. With advanced instrumentation, a high-coverage self-built database, and experienced metabolomics experts, we can provide you with quantitative lipidomics detection services. We are able to perform the quantitative and qualitative analysis of the following lipidomics using LC-MS/MS and GC-MS/MS techniques.

Glycerol phospholipids Phosphatidic acid
Phosphatidylglycerol
Phosphatidylcholine
Phosphatidylserine
Lysophosphatidic acid
Lysophosphatidylcholine
Lysophosphatidylglycerol
Glyceride Monoacylglycerol
Diacylglycerol
Triglyceride
Fatty acyls Free fatty acids
Sphingolipids Phytoceramides
Ceramides
Glycosphingolipid
Sphingosine
Sterollipids Cholesterol esters
Sitosterol esters

How should I prepare and send my samples?

If you require our quantitative lipidomics detection services, please send samples as requested in the form below and contact us.

Sample Type Minimum requirement per sample Storage and transportation
Plant tissue 400 mg Snap freeze in liquid nitrogen.
Store at -80 ℃.
Ship with dry ice.
Plant seeds 40 0mg
Fermentation solution 1 mL

What is it about CD Genomics that is different from others?

  • We have our own quantitative plant lipidome database, which enables the simultaneous detection of more than 20 lipid subclasses.
  • We are able to provide a wide range of data analysis results such as lipid content, chain length, and chain saturation.

Reference

  1. Pranneshraj V, et al. Lipidomics-Assisted GWAS (lGWAS) Approach for Improving High-Temperature Stress Tolerance of Crops. Int J Mol Sci. 2022 Aug 20; 23(16): 9389.
* For Research Use Only. Not for use in diagnostic procedures.
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