Absolute quantitation of a wide range of lipids is vital for lipidomics that is highly important for its applications in biological and clinical research. Metwarebio offers excellent plant quantitative lipidomics service with high throughput, wide coverage, accurate identification and precise quantitation. Elaborated and accurate data analyses suites for lipidomic studies can powerfully accelerate your research.
Lipids are a diverse and ubiquitous group of compounds which have many key biological functions. The diversity in lipid function is reflected by an enormous variation in the structures of lipid molecules. Based on the classification system, lipids have been divided into eight categories: fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, saccharolipids and polyketides, and sterol lipids and prenol lipids, which can be further divided into classes and subclasses. Lipid coverage is crucial in comprehensive lipidomics studies challenged by high diversity in lipid structures and wide dynamic range in lipid levels. Coupling of liquid chromatographic separation to data-dependent MS/MS acquisition for lipidomics can effectively reduce matrix effects and resolve isobaric lipids. Metwarebio has developed a high coverage widely-targeted lipidomics method based on LC-MS/MS. The high coverage of lipids is achieved by integration of the detected lipids derived from 200+ lipid chemical standards, nontargeted UHPLC-HRMS lipidomics analysis of multiple plant matrices, the lipids reported at the open access journal and the predicted lipids speculated on the basis of the structure and chromatographic retention behavior of the known lipids. The in-house lipid database has been finally determined containing 1747 targeted lipids in total (31 subclasses) and can be used for the quantitative lipidomics analysis. The workflow is shown at Quantitative Lipidomics for Plants.
Acyl diacylglyceryl glucuronide
Free fatty acid
An alternative approach of a single stable isotopelabeled internal standards (SIL-IS) and response factors (RFs) was used and developed for the large-scale absolute quantitation of multiple lipid classes. We have chosen 23 chemical standard lipids as SIL-IS, including FFA (16:0)-d31, LPC (16:0)-d31, PA (17:0/17:0), PC (16:0(d31)/18:1), Cer (t18:0/22:0-d3), CoQ10-d9 etc, and have experimentally measured the linear calibration curves of 31 lipid classes using these SIL-IS based an Multiple reaction monitoring-based (MRM) targeted approach. Using calibration curves, RF values for 31 lipid classes have been calculated and are provided absolute quantitation. Finally, a total of 31 lipid classes can be simultaneously absolutely quantified with only 23 SIL-IS lipids, combined with the RF-based approach, which enables large-scale simultaneous identification and absolute quantification of thousands of lipids in a single experiment. The lipidomics method is well validated with satisfactory analytical characteristics in terms of linearity, precision, reproducibility, and recovery for lipidomics profiling. Particularly, it shows better repeatability and higher coverage of lipids than the nontargeted lipidomics method.
Using our lipidomics approach, we can absolutely quantify hundreds of lipids for various biological samples with the levels up to 1079 lipids in arabidopsis thaliana and 878 lipids in oryza sativa. An average of 750 lipids can be detected in plant tissues with good inter-day reproducibility. Overall, we have developed a large-scale lipidomics workflow for the simultaneous identification and absolute quantification of hundreds to thousands of lipids in biological samples.
If you work with plant research and interested in running metabolomics study with plant tissue samples, we offer: