Silver nanoparticles (AgNPs) have been reported to penetrate the central nervous system (CNS) and induce neurotoxicity. However, there is a paucity of understanding of the toxicity of AgNPs and their effect on the blood-brain barrier (BBB) including the underlying molecular mechanism(s) of action. Such information is important for the formulation of new strategies for delivery of biological therapeutics to central nervous system (CNS) targets. Using an in vitro BBB model and mass spectrometry-based proteomics, we investigated alterations in the proteomes of brain endothelial cells and astrocytes at different time points after AgNPs exposure (24 and 48 h). Our data showed that several proteins involved in neurodisorders and neurodegeneration were significantly upregulated in endothelial cells (e.g. 7-dehydrocholesterol reductase, zinc transporters 1 and 6), while proteins responsible for maintaining brain homeostasis were significantly downregulated (e.g anti-oxidative proteins glutathione peroxidase 1 and glutathione peroxidase 4). Many inflammatory pathways were significantly upregulated at 24 h post-AgNPs exposure (C9 pathway), while at 48 h proteins involved in BBB damage and anti-inflammatory responses were upregulated (quinoneoxidoreductase1 and glutamate cysteine ligase catalytic subunit) suggesting that by the later time point, cellular protection pathways had been activated to rescue the cells from AgNPs-induced toxicity. Our study suggests that in the initial stage of exposure, AgNPs exerted direct cellular stress on the endothelial cells by triggering a pro-inflammatory cascade. This study provides detailed insight into the toxic potency of AgNPs on in vitro BBB model and adds to the understanding of the adaptive role of BBB with regards to AgNPs-mediated toxicity.

Nanoparticles (NPs) in contact with protein-containing media such as biological fluids rapidly acquire a surface layer of proteins, known as the protein corona. The protein composition and structural properties of the protein corona are crucial for NP interactions with living cells. Although much has been learned about the protein corona phenomenon, further elucidation could benefit from extensive quantitative proteomics analysis. Herein we report a comprehensive quantitative characterization (>350 proteins) of the corona that formed on 60 nm silver NPs via interaction with human blood plasma, as a function of pH and temperature. By varying the pH and temperature one can access different conformational spaces and charge localizations of the plasma proteins, which in turn provide knowledge pertinent to how the proteome corresponds to binding affinity. Thirty-eight percent of the quantified proteins bind at all temperatures, 47% at all pH values, and of these most persistent proteins, approximately 60% do not significantly change in abundance within the protein corona. Evaluation of 544 protein properties (present in the Kyoto databank) suggests that binding of these proteins to NPs is determined by the extent of hydrophobicity, β-sheet propensity, α-helical structure (and turns), and amino acid composition. Protein binding is promoted by a larger amount of β-sheets, higher hydrophobicity, and a smaller amount of α-helices. Our work enhances researchers' knowledge of a long-standing, vexing aspect of the nano–bio interface.

Proteome characterization relies heavily on tandem mass spectrometry (MS/MS) and is thus associated with instrumentation complexity, lengthy analysis time, and limited duty-cycle. It was always tempting to implement approaches which do not require MS/MS, yet, they were constantly failing in achieving meaningful depth of quantitative proteome coverage within short experimental times, which is particularly important for clinical or biomarker discovery applications. Here, we report on the first successful attempt to develop a truly MS/MS-free method, DirectMS1, for bottom-up proteomics. The method was compared with the standard MS/MS-based data-dependent acquisition approach for proteome-wide analysis using 5-minute LC gradients. Specifically, we demonstrate identification of 1000 protein groups for a standard HeLa cell line digest. The amount of loaded sample was varied in a range from 1 ng to 500 ng, and the method demonstrated 10-fold higher sensitivity. Combined with the recently introduced Diffacto approach for relative protein quantification, DirectMS1 outperforms most popular MS/MS-based label-free quantitation approaches due to significantly higher protein sequence coverage.