Methods

Extrusion procedure: Unilamellar vesicles by extrusion (LUVET) was performed using a Mini-Extruder (Avanti Polar Lipids, Inc.). Pore size of the polycarbonate membrane is 0.1 µm. Heat block was set to 50°C for extrusion. Commercially available 60% egg L-α-phosphatidylcholine (PC) paste (Avanti Polar Lipids, Inc.) was diluted in 5:1 (v:v) water:ethanol at 10% w/v.

Sample preparation: After extrusion, egg solution was extracted using Bligh-Dyer protocol.⁶ Briefly, 2 mL of methanol and 0.8 mL of chloroform were added to 1 mL of the extruded egg solution. SCIEX Lipidyzer™ Platform kits⁷ were added as internal standards and the mixture was left to sit at room temperature for 30 minutes. Then, 1 mL of water and 0.8 mL of chloroform was added, the sample was lightly vortexed, and centrifuged. The lower layer was collected, dried down, and resuspended. 

Chromatography and mass spectrometry: A SCIEX ExionLC™ System equipped with a Luna NH2 column (Phenomenex) and a gradient of 17.5 min were used for separation. MS data were acquired with a SCIEX 7500 System equipped with an OptiFlow® Pro Ion Source and operated using SCIEX OS Software. Details on the chromatographic and MS methods can be obtained from the Comprehensive Targeted Method for Global Lipidomics Screening. ⁵

Data processing: All data were processed using SCIEX OS Software using the AutoPeak algorithm. Automated computation of the Scheduled MRM Alogrithm methods was performed using the sMRM Pro Builder v1.4.⁷

Liposome or LNP characterization

Here, an extruder kit that is commercially available was used to create the liposome formulation. Egg PC paste was used as the natural mixture for extrusion in order to showcase the characterization of lipids from LNPs using LC-MS. Using a 0.1 µm polycarbonate filter, 1 mL of egg solution was passed through the filter and the subsequent mixture containing the liposomes was collected. After lipid extraction, the sample was reconstituted and run using the Comprehensive Targeted Method for Global Lipidomics Screening.⁵ The method is optimized for a targeted assay on a broad panel of 20 lipids classes containing over 2000 transitions. The sMRM list is customizable enabling the addition or removal of entire classes or individual lipid species based on the matrix or application. In Figure 2, the pie chart represents the number of lipid species found by lipid class. It provides a rough distribution of the lipid makeup of the egg matrix after extrusion.

Quantification can be necessary when shifting from a natural product to a defined liposome or LNP. Historically, relative quantification with one internal standard per class using Avanti’s SPLASH mix has been the industry standard while analyzing large lipid panels. However, the differential fragmentation inherent to lipids with varying chain lengths and degrees of unsaturation cannot be corrected with a single internal standard alone. To close that gap, Lipidyzer Platform standards were designed providing accurate quantification for a variety of lipid classes (Table 1). ⁸ The kit contains 54 unique labeled internal standards that spans 13 lipid classes. With multiple standards per class that have variable chain lengths and degrees of unsaturation, the quantitative bias for individual molecular species is less than 10%.⁸ Table 1 displays the concentrations for the class of LPL using the internal standards from the Lipidyzer Platform kit.

To successfully implement a large panel lipidomic screen, a large dynamic range of the assay is essential. With the sensitivity of the SCIEX 7500 System, >5.5 orders of magnitude dynamic range were achieved (Figure 3). Another issue to overcome is the extensive isobaric overlap between different lipid classes and species. Using a normal phase gradient compared to reverse phase allows the user to achieve class separation and minimizes interferences from isobaric species (Figure 4). With the established method, a complete snapshot of the lipid composition can be detailed for a formulated liposome or LNP. Employing the sMRM Pro Builder template on the profiling data enables a user to further filter results. By filtering the data by total area, lipid species of each class based on a user-specified area threshold are shown (Figure 5). By filtering the panel containing over 2100 MRMs to focus on LPL (such as LPC or lysophosphatidylethanolamines, known as LPE), oxidized lipids or other undesired elements that can contribute to an unstable liposome, users can modify the MRM list easily based on their matrix or focus for analysis.

Within the studied liposome sample, 21 LPL were identified. Several medium- and long-chain polyunsaturated could be detected and quantified in the liposome sample such as LPC(18:3), LPE(20:4), LPC(22:6) and LPE(22:5). These LPL have been implicated in instability or leaky lipid nanoparticles.⁹ Therefore detection, proper identification, and quantification of this class of compounds can be key to successful drug delivery vehicle formulation by monitoring these lipids during the development and stability studies of LNPs.

Conclusion
 

• Unparalleled sensitivity and dynamic range for broad profiling of liposomes and lipid nanoparticles was achieved with the SCIEX 7500 System
  
  
• The presented MRM assay was proven to be comprehensive and customizable providing a targeted and flexible solution to lipid profiling
  
  
• The combination of advanced hardware and streamlined software presents a cutting-edge solution for targeted quantification in a high-throughput workflow
  

References
 

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