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Characterization of mRNA Lipid Nanoparticles by Electron Density Mapping Reconstruction: X-ray Scattering with Density from Solution Scattering (DENSS) Algorithm

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Abstract

Purpose

This study aimed to test the feasibility of using Small Angle X-ray Scattering (SAXS) coupled with Density from Solution Scattering (DENSS) algorithm to characterize the internal architecture of messenger RNA-containing lipid nanoparticles (mRNA-LNPs).

Methods

The DENSS algorithm was employed to construct a three-dimensional model of average individual mRNA-LNP. The reconstructed models were cross validated with cryogenic transmission electron microscopy (cryo-TEM), and dynamic light scattering (DLS) to assess size, morphology, and internal structure.

Results

Cryo-TEM and DLS complemented SAXS, revealed a core–shell mRNA-LNP structure with electron-rich mRNA-rich region at the core, surrounded by lipids. The reconstructed model, utilizing the DENSS algorithm, effectively distinguishes mRNA and lipids via electron density mapping. Notably, DENSS accurately models the morphology of the mRNA-LNPs as an ellipsoidal shape with a "bleb" architecture or a two-compartment structure with contrasting electron densities, corresponding to mRNA-filled and empty lipid compartments, respectively. Finally, subtle changes in the LNP structure after three freeze–thaw cycles were detected by SAXS, demonstrating an increase in radius of gyration (Rg) associated with mRNA leakage.

Conclusion

Analyzing SAXS profiles based on DENSS algorithm to yield a reconstructed electron density based three-dimensional model can be a useful physicochemical characterization method in the toolbox to study mRNA-LNPs and facilitate their development.

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Data Availability

Raw SAXS data were included in the supporting information and also available upon request.

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Acknowledgements

We acknowledge the asistance of Thomas Weiss in performing synchrotron SAXS experiment. Use of the Stanford Synchrotron Radiation Lightsource (SSRL), SLAC National Accelerator Laboratory, is supported by the U.S. Department of Energy (DoE), Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515. The SSRL Structural Molecular Biology Program is supported by the DOE Office of Biological and Environmental Research, and by the National Institutes of Health, National Institute of General Medical Sciences (P30GM133894). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of NIGMS or DoE.

Funding

This work was supported by a Sponsored Research Agreement from TFF Pharmaceuticals Inc. (to ROW and ZC).

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Authors and Affiliations

  1. Division of Molecular Pharmaceutics and Drug Delivery, College of Pharmacy, The University of Texas at Austin, Austin, TX, 78712, USA

    Huy M. Dao, Khaled AboulFotouh, Zhengrong Cui & Robert O. Williams III

  2. Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX, USA

    Aasim Faheem Hussain & Alexander E. Marras

  3. Materials Science and Engineering Graduate Program, Texas Materials Institute, The University of Texas at Austin, Austin, TX, USA

    Alexander E. Marras

  4. Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX, USA

    Alexander E. Marras

  5. McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX, USA

    Keith P. Johnston

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The manuscript was written with the contributions of all authors. / All authors have approved the final version of the manuscript.

Corresponding authors

Correspondence to Zhengrong Cui or Robert O. Williams III.

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Competing Interest

ZC and ROW report financial support by TFF Pharmaceuticals, Inc. The terms have been reviewed and approved by UT Austin in accordance with its institutional policy on objectivity in research. ZC reports a relationship with TFF Pharmaceuticals, Inc. that includes equity or stocks and funding grants. ROW reports a relationship with TFF Pharmaceuticals, Inc. that includes consulting or advisory, equity or stocks, and funding grants. ZC, ROW, and KJP have patent(s) and/or patent applications related to thin-film freezing.

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Dao, H.M., AboulFotouh, K., Hussain, A.F. et al. Characterization of mRNA Lipid Nanoparticles by Electron Density Mapping Reconstruction: X-ray Scattering with Density from Solution Scattering (DENSS) Algorithm. Pharm Res 41, 501–512 (2024). https://doi.org/10.1007/s11095-024-03671-9

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