br Liposomes recovered from plasma were separated

Liposomes recovered from plasma were separated form excess plasma proteins by size exclusion chromatography followed by mem-brane ultrafiltration as we have previously described [10–12].
4.6. Size and zeta potential measurements using dynamic light scattering (DLS)
Liposome size and surface charge were measured using Zetasizer Nano ZS (Malvern, Instruments, UK).
4.7. Transmission electron microscopy (TEM)
Liposomes were visualized with transmission electron microscopy (FEI Tecnai 12 BioTwin) before and after corona formation using Carbon Film Mesh Copper Grid (CF400-Cu, Electron Microscopy Science), after staining with aqueous uranyl acetate solution 1% [10].
4.8. SDS-PAGE electrophoresis
Corona proteins associated with 0.025 μM of liposomes and plasma samples (5 μl) were loaded and run in a 4–20% Novex® Tris-Glycine SDS Running Buffer (ThermoFisher Scientific), according to manufacturer's instructions. The gels were stained with Imperial Gel Staining reagent (Sigma Life Science).
4.9. Quantification of adsorbed proteins
Proteins associated with recovered liposomes were quantified by BCA Protein assay kit and the amount of liposomes recovered by Stewart assay [10–12]. Pb values, expressed as μg of protein/μmole of lipid were calculated and presented as the average ± standard  Biomaterials 188 (2019) 118–129
deviation (n = 3 biological replicates, n = 3 mice/replicate). For the comparison of Pb values (Fig. 1C) statistical analysis of the data was performed using GraphPad Prism 7.02 software. Unpaired two-tailed t-test was performed and p values < 0.05 were considered significant.
4.10. Mass spectrometry
In-gel Oxaliplatin of corona (40 μg) and plasma (5 μl) proteins was performed prior to LC-MS/MS analysis, as we have previously described [11–13]. UltiMate® 3000 Rapid Separation LC (RSLC, Dionex Corpora-tion, Sunnyvale, CA) was coupled to an Orbitrap Fusion™ (Thermo Fisher Scientific, Waltham, MA) mass spectrometer.
4.11. Mass spectrometry data analysis
Data produced were searched using Mascot (Matrix Science UK), against the [SwissProt_2016_04 database]. The Scaffold software (ver-sion 4.3.2, Proteome Software Inc.) was used to validate MS/MS based peptide and protein identifications and for relative quantification based on spectral counting (Figs. 2 and 4). Semi quantitative assessment of the protein amounts was conducted using normalized spectral counting (50% peptide probability, 99% protein probability, at least 2 identified proteins), as we have previously reported [10–13]. Heatmaps of RPA values were prepared using Plotly 2.0 software.
To statistically compare proteins identified in the coronas formed in healthy and tumor-bearing mice (Figs. 3 and 5), MS peak intensities were analysed using Progenesis LC-MS software (version 3.0; Nonlinear Dynamics). Data was filtered to a 1% false discovery rate (FDR). The peptide intensities were compared between groups by one way analysis of variance (ANOVA, p < 0.05 for statistical significance).
Mass Spectrometry data were analysed through the use of QIAGEN's Ingenuity® Pathway Analysis (IPA®, QIAGEN Redwood City, www. qiagen.com/ingenuity). Diseases and functions IPA tool was used to identify proteins involved in melanoma and lung-carcinoma associated proteins. The biomarker overlay IPA tool was then used to identify proteins described in the literature as potential biomarkers for mela-noma and lung cancer.
4.12. Species-specific peptide identification
Mass spectrometry datasets were analysed using Mascot and Scaffold as described above, and peptide lists were generated with ei-ther mouse or human taxonomy selected. Peptides were classified as being unique to mouse or human databases, or common to both using in-house code (Mathematica version 11.0.1; Wolfram Research, Champaign, IL) [37]. Peptide species were checked using the BLAST protein database (National Center for Biotechnology Information, Be-thesda, MD). We considered the detection of human-sourced protein material to be evidenced by the detection of two-or-more human-spe-cific peptides per protein identity. Peptides were aggregated over tri-plicate samples; any peptides that were also detected in triplicate mouse-only control samples (i.e. false positives) were removed from consideration; peptides differing between mouse and human by only a single amino acid substitution were also not considered.