Lipid nanoparticle characterization: electrophoretic light scattering

In this application note, Field Application Scientist Dr Jonathan Mehtala describes how pharmaceutical scientists are using electrophoretic light scattering (ELS) to characterize lipid nanoparticles (LNPs) and why you should be using it. Reflecting on a recent publication that investigates the characterization of viral and non-viral vectors using multiple Malvern Panalytical technologies, Dr Mehtala shows how the Zetasizer Advance Ultra was used to measure the zeta potential of two mRNA-LNP* samples.

If you are a scientists or project leader working on the design, process and formulation development of lipid nanoparticles for drug or vaccine delivery - this application note will show you how the Zetasizer Advance can help you     is essential reading for you.

*LNP: Lipid nanoparticle

Author: Dr Jonathan Mehtala, Team Leader – Biophysical Characterization

Introduction

Following a recent publicationi investigating the characterization of viral and non-viral drug delivery vectors, this application note takes a close look at how researchers used the Zetasizer Advance Ultra to measure the zeta potential of two mRNA-LNP samples.

What are lipid nanoparticles

Lipid nanoparticles (LNPs) are the most common non-viral vector used in gene therapy and mRNA-based vaccines. Following decades of research and development their acceptance as a drug delivery vector has been accelerated by the approval of multiple mRNA-LNPs COVID-19 vaccines. LNPs are composed of at least four components: 

  1. phospholipids that can be neutral, cationic, anionic, or zwitterionic 
  2. cholesterol and other naturally occurring hydrophobic molecules
  3. a therapeutic transgene, typically nucleic acid biopolymers like DNA or RNA
  4. lipid-anchored polyethylene glycol (PEG), which “hides” the LNP surface from immune detection, slowing removal by the body

 

What are lipid nanoparticles

Lipid nanoparticles (LNPs) are the most common non-viral vector used in gene therapy and mRNA-based vaccines. Following decades of research and development their acceptance as a drug delivery vector has been accelerated by the approval of multiple mRNA-LNPs COVID-19 vaccines. LNPs are composed of at least four components: 

  • phospholipids that can be neutral, cationic, anionic, or zwitterionic 
  • cholesterol and other naturally occurring hydrophobic molecules
  • a therapeutic transgene, typically nucleic acid biopolymers like DNA or RNA
  • lipid-anchored polyethylene glycol (PEG), which “hides” the LNP surface from immune detection, slowing removal by the body

[LNP-image.png] LNP-image.png

 Figure 1: The basic structure and compositions of the mRNA-LNP characterized in this study.


Why measure the zeta potential of LNP formulations?

Zeta potential is a charge property that predicts nanoparticle stability and correlates to other properties. It is used in drug development to compare stability between buffer formulations, lipid composition, and for basic nanomaterials. 

Charged particles exert an electrostatic inter-particle repulsive force that increases colloidal stability. In the absence of a strong stabilizing electrostatic force, it is common to add steric stabilizers in the form of non-ionic surfactants such as PEG to the liquid formulation or particle surface.  For pharmaceutical drug products, poor stability can result in undesired outcomes, such as short shelf-life, loss of efficacy, and increased safety risksii.

How is Zetasizer Ultra applied in LNP research & manufacture?

Zetasizer Ultra utilizes dynamic light scattering (DLS), multi-angle dynamic light scattering (MADLS), static light scattering (SLS), and electrophoretic light scattering (ELS) to measure particle properties such as size, aggregation, thermal aggregation point, protein interaction parameters, charge, and zeta potential.

Zeta potential (an indicator of apparent surface charge in a medium) is key to understanding the stability of lipid nanoparticles in solution. It also provides information about surface chemistry of the structure – e.g. if you were to coat the surface your vector, zeta potential can provide information about the effects of this coating. A high zeta potential measurement (>+30) indicates a stable dispersion, while a low measurement (0 - +10) indicates electrostatic instability – the closer to 0 the bigger the problem. This may be as you have other types of stabilization, e.g. steric stability, such as PEGylation

(To read about zeta potential measurements read this technical note >>)


Methods for analyzing zeta potential

Two mRNA-LNP formulations were used, LNP1 and LNP2iii. Electrophoretic light scattering (ELS) measurements of the lipid nanoparticles samples were measured using a Zetasizer Ultra Red instrument equipped with a He-Ne laser at a wavelength of 633 nm and maximum power of 10 mW. Amounts of 700 µL of the samples were introduced into a folded capillary cell, DTS1070iv, using the Diffusion Barrier method (see below). The duration of 35 zeta potential measurements was manually set up, with 10 sub-runs per measurement.

pH titrations of the mRNA-LNP formulations, prepared in 10 mM NaCl (10 mL sample volume), were performed with the multipurpose titrator 3 (MPT3) accessory, degasser and Zetasizer Ultra Red at a temperature of 25°C.
 

The diffusion barrier (DB) method

The diffusion barrier (DB) methodv is a patented of taking zeta potential measurements that allows you to reduce sample volume.  Using the DB method to load the DTS1070 folded capillary zeta potential cuvette only 20-50 microliters of sample were required.  Using such a small aliquot means the sample does not come into contact with the capillary cell electrodes, preserving the integrity of the sample. 


Results

The zeta potential for LNP formulation samples in PBS were mRNA-LNP1: -19.5 mV and mRNA-LNP2: -6.62 mVBoth measurements showed excellent repeatability with standard deviations of only 1.32 mV and 1.47 mV, respectively (Table 1).

MeasurementZeta Potential (mV)z-Average Diameters (nm)

mRNA-LNP1
mRNA-LNP2mRNA-LNP1mRNA-LNP2
1-20.0-5.3568.999.9
2-18.00-6.3069.7102.6
3-20.5-8.2370.0102.8
4--69.9102.3
5--70.2103.1
Mean-19.5-6.6369.7102.1

Standard
deviation

1.32

1.47

0.50

1.29

Table 1: Zeta potential mean values (in mV) and Z-average diameters (in nm) for the mRNA-LNP1 and mRNA-LNP2 samples measured in PBS using the diffusion barrier method

The MPT-3 auto titrator was used to measure zeta potential over a pH range of 2.5 to 9.5.  At high and low pH in 10 mM NaCl, the zeta potential for mRNA-LNP1 and mRNA-LNP2 were virtually identical, at approximately +19 mV and -35 mV, respectively.  However, the isoelectric points (pI) of the two samples were different, with mRNA-LNP1 having a pI at pH 5.89 and mRNA-LNP2 at pH 5.21 (Figure 2).

[Figure showing a plot of zeta potential values.png] Figure showing plot of zeta potential values.png

Figure 2. A plot of the zeta potential values (in mV) as a function of pH for mRNA-LNP1 and mRNA-LNP2 samples prepared in 10 nM NaCl.

Discussion

Zeta potential is often regarded as a charge property related only to the particle. However, many factors influence the zeta potential of the particle and the buffer conditions. Examples of LNP properties that influence zeta potential are the type and amount of charged lipids, charge density, surface PEGylation, and nucleic acid cargo located either inside or on the LNP surface. Examples of buffer properties that can influence zeta potential are ionic strength, salt type and amount, pH, and other additives such as sugars, amino acids, and non-ionic surfactants.

At low and high pH, both mRNA-LNP samples had approximately the same zeta potential. However, In the middle pH ranges, mRNA-LNP1 was consistently more negatively charged than mRNA-LNP2. Under identical buffer conditions, the cause of this charge difference can only be due to differences in either the lipid composition or mRNA.  Most of the charge associated with a mRNA-LNP will be in the phosphate backbone of the nucleic acid cargo or the charged headgroups of the phospholipids, either as cationic, anionic, or zwitterionic functional groups.

These results predict that mRNA-LNP1 is more stable and/or contains a larger mRNA therapeutic payload, both of which indicate that it is a superior drug candidate to mRNA-LNP2.

Further reading

  • Explore how differential scanning calorimetry (DSC) is used as an orthogonal technique to DLS for greater insights about mRNA-LNP formulations: read more >>
  • Read the full peer-reviewed paper on which this application note is based: read more >>
  • Discover more expert tips and advice on LNP characterization in the Vector Analytics Acceleration Center. Learn more >>

Featured and related products

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MicroCal PEAQ DSCView here




References

N. Markova, et al. Vaccines 10, 49 (2022).  
ii Sanyal, G., Särnefält, A. & Kumar, A. Considerations for bioanalytical characterization and batch release of COVID-19 vaccines. npj Vaccines 6, 53 (2021). https://doi.org/10.1038/s41541-021-00317-4.
iiimRNA-LNPs were provided by SINTEF Industri (Department of Biotechnology and Nanomedicine, Trondheim, Norway), and made as described in detail elsewhere. In short, two formulations of mRNA-LNPs were synthetized using Nanoassembler (Precision Nanosystems) with stock lipid solutions of cholesterol, D SPC, and PEG2000-DMG (from Avanti Polar) at 10 mg/mL and of MC3 and SM102 (from Organix) at 20 mg/mL, respectively called LNP1 and LNP2. FLuc CleanCap® FLuc mRNA (5moU) used to formulate the LNPs in this study was purchased from Tebu-Bio (Roskilde, Denmark).
iv DTS1070, Malvern Panalytical Ltd., Malvern, UK.
The Diffusion Barrier Technique for Accurate and Reproducible Protein Mobility Measurement.

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