Analysis of plasma protein adsorption onto DC-Chol-DOPE cationic liposomes by HPLC-CHIP coupled to a Q-TOF mass spectrometer

Anna Laura Capriotti, Giulio Caracciolo, Giuseppe Caruso, Chiara Cavaliere, Daniela Pozzi, Roberto Samperi, Aldo Laganà

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

Plasma protein adsorption is regarded as a key factor in the in vivo organ distribution of intravenously administered drug carriers, and strongly depends on vector surface characteristics. The present study aimed to characterize the "protein corona" absorbed onto DC-Chol-DOPE cationic liposomes. This system was chosen because it is one of the most efficient and widely used non-viral formulations in vitro and a potential candidate for in vivo transfection of genetic material. After incubation of human plasma with cationic liposomes, nanoparticle-protein complex was separated from plasma by centrifugation. An integrated approach based on protein separation by one-dimensional 12% polyacrylamide gel electrophoresis followed by the automated HPLC-Chip technology coupled to a high-resolution mass spectrometer was employed for protein corona characterization. Thirty gel lanes, approximately 2 mm, were cut, digested and analyzed by HPLC-MS/MS. Fifty-eight human plasma proteins adsorbed onto DC-Chol-DOPE cationic liposomes were identified. The knowledge of the interactions of proteins with liposomes can be exploited for future controlled design of colloidal drug carriers and possibly in the controlled creation of biocompatible surfaces of other devices that come into contact with proteins in body fluids. © 2010 Springer-Verlag.
Original languageEnglish (US)
Pages (from-to)2895-2903
Number of pages9
JournalAnalytical and Bioanalytical Chemistry
Volume398
Issue number7-8
DOIs
StatePublished - Sep 22 2010
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-F1-036-32
Acknowledgements: This publication is based on work supported by Award No. KUK-F1-036-32, made by King Abdullah University of Science and Technology (KAUST).A special acknowledgment is given to Agilent Technologies and Agilent staff members, for their invaluable help and technical assistance. In particular, the authors wish to thank Alberto Stocco (Agilent Technologies) for his technical assistance and his infinite helpfulness.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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