Core-shell NaHoF4@TiO2 NPs: A labelling method to trace engineered nanomaterials of ubiquitous elements in the environment

Understanding the fate and behavior of nanoparticles (NPs) in the natural environment is important to assess their potential risk. Single particle inductively coupled plasma mass spectrometry (spICP-MS) allows for the detection of NPs at extremely low concentrations, but the high natural background of the constituents of many of the most widely utilized nanoscale materials makes accurate quantification of engineered particles challenging. Chemical doping, with a less naturally abundant element, is one approach to address this; however, certain materials with high natural abundance, such as TiO2 NPs, are notoriously difficult to label and differentiate from natural NPs. Using the low abundance rare earth element Ho as a marker, Ho-bearing core -TiO2 shell (NaHoF4@TiO2) NPs were designed to enable the quantification of engineered TiO2 NPs in real environmental samples. The NaHoF4@TiO2 NPs were synthesized on a large scale (gram), at relatively low temperatures, using a sacrificial Al(OH)3 template that confines the hydrolysis of TiF4 within the space surrounding the NaHoF4 NPs. The resulting NPs consist of a 60 nm NaHoF4 core and a 5 nm anatase TiO2 shell, as determined by TEM, STEM-EDX mapping, and spICPMS. The NPs exhibit excellent detectability by spICP-MS at extremely low concentrations (down to 1 × 10−3 ng/L) even in complex natural environments with high Ti background

A ScienceOpen collection of NanoSafety Cluster publications

Preprint describing a ScienceOpen collection of literature generated by NanoSafety Cluster projects

Mechanisms for cellular uptake of nanosized clinical MRI contrast agents

Engineered Nanomaterials (NMs), such as Superparamagnetic Iron Oxide Nanoparticles (SPIONs), offer significant benefits in a wide range of applications, including cancer diagnostic and therapeutic strategies. However, the use of NMs in biomedicine raises safety concerns due to lack of knowledge on possible biological interactions and effects. The initial basis for using SPIONs as biomedical MRI contrast enhancement agents was the idea that they are selectively taken up by macrophage cells, and not by the surrounding cancer cells. To investigate this claim, we analyzed the uptake of SPIONs into well-established cancer cell models and benchmarked this against a common macrophage cell model. In combination with fluorescent labeling of compartments and siRNA silencing of various proteins involved in common endocytic pathways, the mechanisms of internalization of SPIONs in these cell types has been ascertained utilizing reflectance confocal microscopy. Caveolar mediated endocytosis and macropinocytosis are both implicated in SPION uptake into cancer cells, whereas in macrophage cells, a clathrin-dependant route appears to predominate. Colocalization studies confirmed the eventual fate of SPIONs as accumulation in the degradative lysosomes. Dissolution of the SPIONs within the lysosomal environment has also been determined, allowing a fuller understanding of the cellular interactions, uptake, trafficking and effects of SPIONs within a variety of cancer cells and macrophages. Overall, the behavior of SPIONS in non-phagocytotic cell lines is broadly similar to that in the specialist macrophage cells, although some differences in the uptake patterns are apparent.</p

Understanding the Significance of Sample Preparation in Studies of the Nanoparticle Metabolite Corona

The adsorption of metabolites to the surface of nanomaterials is a growing area of interest in the field of bionanointeractions. Like its more-established protein counterpart, it is thought that the metabolite corona has a key role in the uptake, distribution, and toxicity of nanomaterials in organisms. Previous research has demonstrated that nanomaterials obtain a unique metabolite fingerprint when exposed to biological matrices; however, there have been some concerns raised over the reproducibility of bionanointeraction research due to challenges in dispersion of nanomaterials and their stability. As such, this work investigates a much-overlooked aspect of this field, i.e., sample preparation, which is vital to the accurate, reproducible, and informative analysis of the metabolite corona. The impact of elution buffer pH, volume, and ionic strength on the metabolite corona composition acquired by uncapped and polyvinylpyrrolidone (PVP)-capped TiO2 from mixtures of cationic and anionic metabolites was studied. We demonstrate the temporal evolution of the TiO2 metabolite corona and the recovery of the metabolite corona, which resulted from a complex biological matrix, in this case human plasma. This work also demonstrates that it is vital to optimize sample preparation for each nanomaterial being investigated, as the metabolite recovery from Fe3O4 and Dispex-capped TiO2 nanomaterials is significantly reduced compared to the aforementioned uncapped and PVP-capped TiO2 nanomaterials. These are important findings for future bionanointeraction studies, which is a rapidly emerging area of research in nanoscience

What the Cell “Sees” in Bionanoscience

What the biological cell, organ, or barrier actually “sees” when interacting with a nanoparticle dispersed in a biological medium likely matters more than the bare material properties of the particle itself. Typically the bare surface of the particle is covered by several biomolecules, including a select group of proteins drawn from the biological medium. Here, we apply several different methodologies, in a time-resolved manner, to follow the lifetime of such biomolecular “coronas” both in situ and isolated from the excess plasma. We find that such particle−biomolecule complexes can be physically isolated from the surrounding medium and studied in some detail, without altering their structure. For several nanomaterial types, we find that blood plasma-derived coronas are sufficiently long-lived that they, rather than the nanomaterial surface, are likely to be what the cell sees. From fundamental science to regulatory safety, current efforts to classify the biological impacts of nanomaterials (currently according to bare material type and bare surface properties) may be assisted by the methodology and understanding reported here

Cellular uptake and localisation of cerium dioxide NPs visualized by RCM, FCM, SIM and TEM.

Reflectance and TEM overlays of HeLa cells treated with cerium dioxide NPs. The ultrastructure of the cell is preserved and the sub-cellular localisation of NPs is evidenced by the lysosomal fluorescence stain (D). The TEM image has a section thickness of 150 nm. RCM overlay has a theoretical optical thickness of ~480 nm. R-SIM has an optical thickness of approximately the measured FWHMaxial which is 685 nm. Adjacent image sections were combined so that the thickness across modalities was as consistent as possible. Reflectance intensity arising in both RCM (A: Green) and SIM (B: Red) corresponds to regions detected by TEM. Overlays of DAPI nuclear and CTDR cytoplasmic stain (C) are shown. LysoTracker DND-99 stain (D: Blue) shows the localisation of detected NPs in lysosomes. White boxes show regions of correlation between all three modalities with increased magnification.</p

Comparison of the image acquisition specifications for each modality.

<p>Table 1.provides a comparison of the image acquisition specifications for each modality.</p

Correlation of data obtained from RCM and SIM reflectance.

<p>Maximum intensity Z-projection images of a HeLa cells treated with cerium dioxide NPs, acquired with RCM and R-SIM using identical 100X, 1.49 NA objective. RCM imaging volume is 3.6 μm and SIM 4 μm. Images A) (RCM) and B) (R-SIM) show CTDR (red) cytoplasmic stain, DAPI (blue) nuclear stain and NP signal (grey). Overlay of the cerium dioxide NP regions show particles detected in RCM (blue) and SIM (grey) in both the raw (C) and processed (D) images. White boxes display a sample of regions where RCM detects one spot and SIM detects multiple spots, illustrating the enhanced resolution of SIM. Intensity line scans of RCM (E) and R-SIM (F) show the decrease in peak width in SIM and the detection of two peaks where RCM detects one. The average total number of regions detected via each technique was computed (47 and 68 for RCM and R-SIM respectively) (G). The percentage of ‘regions’ or ‘connected components’ visualised with each modality, RCM and R-SIM, that are also seen in the other modality (54% and 74% respectively), were computed automatically using MATLAB as detailed in the methods section using 27 cells from multiple experiments performed on separate days (H). The means and STD are plotted. Comparison of the size distribution of the FWHM of 100 / 125 regions for RCM and R-SIM respectively are shown (I), with a fitted probability density function.</p

RCM allows visualisation of NP uptake within cancer cell models.

NP uptake can be visualised in HeLa cells treated with cerium dioxide NPs (65 cells) or SPIONs (51 cells) comparted to untreated control cells (25 cells). Images show maximum intensity Z-projections of cells stained with Cell Tracker Deep Red (CTDR) (red), 4’,6-diamdino-2phenylindeo (DAPI) nuclear stain (blue) and NP reflectance signal (grey). Control cells show no high intensity reflective spots. The raw intensity reflectance images show background reflectance in both control and treated cells (top panel). Following post processing, regions of high intensity signal are segmented from background signal (middle panel). Overlay of fluorescence stains and segmented reflectance NP signal (grey) (bottom panel).</p

Comparison of Confocal and Super-Resolution Reflectance Imaging of Metal Oxide Nanoparticles - Fig 1

<p><b>Electron micrographs of A) cerium dioxide NPs, B) SPIONs, and C) Non-treated cells.</b> The top panel depicts 70 nm ultrathin sections, the standard TEM mode, while the bottom panel uses 150 nm sections. Ultrathin and semi-thick sections can thus be successfully imaged. Thin sections give rise to a crisper image, with increased contrast visible at organelle boundaries. Thick sections have slightly less contrast due to the denser area being imaged but allow alignment with confocal slices (see below).</p