DNA-Loaded Cationic Liposomes Efficiently Function as a Vaccine against Malarial Proteins
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Author(s)
Fotoran, Wesley L.
Santangelo, Rachele
de Miranda, Beatriz N.M.
Wunderlich, Gerhard
Irvine, Darrell J
Date Issued
August 2017
Journal
Molecular Therapy - Methods & Clinical Development
Publisher
Elsevier BV
Citation
Fotoran, Wesley L. et al. “DNA-Loaded Cationic Liposomes Efficiently Function as a Vaccine Against Malarial Proteins.” Molecular Therapy - Methods & Clinical Development 7 (December 2017): 1–10 © 2017 The Author(s)
Version
Final published version
Abstract
The delivery of antigens as DNA vaccines is an efficient alternative to induce immune responses against antigens, which are difficult to produce in recombinant form. However, the delivery of naked DNA is ineffective or relies on sophisticated ballistic devices. Here, we show a combination of liposome application and naked DNA vaccine that successfully overcomes these problems. Upon entrapment of plasmids encoding different antigens in cationic particles, transfection efficiencies similar to commercial kits were achieved in in vitro cell cultures. The liposome-based approach provided strong humoral responses against three malarial antigens, namely the Circumsporozoite protein and the C terminus of merozoite surface protein 1 from Plasmodium vivax (titers 104or 103–104, respectively) and P. falciparum Rhoptry antigen 5 from Plasmodium falciparum (titers 103–104). When employed in P. falciparum growth-inhibition assays, antibodies demonstrated consistent reinvasion-blocking activities that were dose dependent. Liposome-formulated DNA vaccines may prove useful when targets cannot be produced as recombinant proteins and when conformation-dependent and highly specific antibodies are mandatory. Keywords: cationic liposomes; DNA vaccine; malaria
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Koch Institute for Integrative Cancer Research at MIT
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1016/J.OMTM.2017.08.004
