Potential application of Au core labeling for tracking Ag nanoparticles in the aquatic and biological system

Spatiotemporal Mapping of the Evolution of Silver Nanoparticles in Living Cells

Bioaccumulated silver nanoparticles (AgNPs) can undergo transformation and release toxic Ag+, which can be further reduced and form secondary AgNPs (Ag0NPs). However, the intricate interconversions among AgNPs, Ag+, and Ag0NPs remain speculative. Herein, we developed a bioimaging method by coupling the aggregation-induced emission method with the label-free confocal scattering and hyperspectral imaging techniques to quantitatively visualize the biodistribution and biotransformation of AgNPs, Ag0NPs, and Ag+ in living cells. We demonstrated that AgNPs were first dissolved in the medium, and the released Ag+ was converted into Ag0NPs with the presence of algal extracellular polymeric substances and light. Under these conditions, AgNPs alone accounted for 12.4% of the total AgNP toxicity, a percentage comparable to that of Ag0NPs (15.6%). However, Ag+ remained the primary contributor to overall AgNP toxicity. Additionally, we found that about 9.00% of the accumulated AgNPs within the algal cells were transformed after 24 h exposure. Of these transformed AgNPs, 4.70% remained as Ag+ forms (located in the apical region, nucleus, and pyrenoid), while 4.30% persisted as Ag0NP forms (located in the cytosol) that were only detectable after a 4 h exposure. We further showed that AgNP exposure upregulated algal glutathione production with a 38.3-fold increase in glutathione reductase activity, which potentially resulted in Ag0NP formation at the active site. Overall, this study differentiated the toxicity of AgNPs, Ag+, and Ag0NPs and directly visualized the ongoing transformation and translocation of AgNPs, Ag+, and Ag0NPs within living cells, which are critical in unveiling the toxicity mechanisms of AgNPs.

Tracking the Cellular Degradation of Silver Nanoparticles: Development of a Generic Kinetic Model

Understanding the degradation of nanoparticles (NPs) after crossing the cell plasma membrane is crucial in drug delivery designs and cytotoxicity assessment. However, the key factors controlling the degradable kinetics remain unclear due to the absence of a quantification model. In this study, subcellular imaging of silver nanoparticles (AgNPs) was used to determine the intracellular transfer of AgNPs, and single particle ICP-MS was utilized to track the degradation process. A cellular kinetic model was subsequently developed to describe the uptake, transfer, and degradation behaviors of AgNPs. Our model demonstrated that the intracellular degradation efficiency of AgNPs was much higher than that determined by mimicking testing, and the degradation of NPs was highly influenced by cellular factors. Specifically, deficiencies in Ca or Zn primarily decreased the kinetic dissolution of NPs, while a Ca deficiency also resulted in the retardation of NP transfer. The biological significance of these kinetic parameters was strongly revealed. Our model indicated that the majority of internalized AgNPs dissolved, with the resulting ions being rapidly depurated. The release of Ag ions was largely dependent on the microvesicle-mediated route. By changing the coating and size of AgNPs, the model results suggested that size influenced the transfer of NPs into the degradation process, whereas coating affected the degradation kinetics. Overall, our developed model provides a valuable tool for understanding and predicting the impacts of the physicochemical properties of NPs and the ambient environment on nanotoxicity and therapeutic efficacy.

Using Machine Learning to Predict Adverse Effects of Metallic Nanomaterials to Various Aquatic Organisms

The wide production and use of metallic nanomaterials (MNMs) leads to increased emissions into the aquatic environments and induces high potential risks. Experimentally evaluating the (eco)toxicity of MNMs is time-consuming and expensive due to the multiple environmental factors, the complexity of material properties, and the species diversity. Machine learning (ML) models provide an option to deal with heterogeneous data sets and complex relationships. The present study established an in silico model based on a machine learning properties-environmental conditions-multi species-toxicity prediction model (ML-PEMST) that can be applied to predict the toxicity of different MNMs toward multiple aquatic species. Feature importance and interaction analysis based on the random forest method indicated that exposure duration, illumination, primary size, and hydrodynamic diameter were the main factors affecting the ecotoxicity of MNMs to a variety of aquatic organisms. Illumination was demonstrated to have the most interaction with the other features. Moreover, incorporating additional detailed information on the ecological traits of the test species will allow us to further optimize and improve the predictive performance of the model. This study provides a new approach for ecotoxicity predictions for organisms in the aquatic environment and will help us to further explore exposure pathways and the risk assessment of MNMs.

Combining surface-accessible Ag and Au colloidal nanomaterials with SERS for in situ analysis of molecule-metal interactions in complex solution environments

The interactions between molecules and noble metal nanosurfaces play a central role in many areas of nanotechnology. The surface chemistry of noble metal surfaces under ideal, clean conditions has been extensively studied; however, clean conditions are seldom met in real-world applications. We developed a sensitive and robust characterization technique for probing the surface chemistry of nanomaterials in the complex environments that are directly relevant to their applications. Surface-enhanced Raman spectroscopy (SERS) can be used to probe the interaction of plasmonic nanoparticles with light to enhance the Raman signals of molecules near the surface of nanoparticles. Here, we explain how to couple SERS with surface-accessible plasmonic-enhancing substrates, which are capped with weakly adsorbing capping ligands such as citrate and chloride ions, to allow molecule-metal interactions to be probed in situ and in real time, thus providing information on the surface orientation and the formation and breaking of chemical bonds. The procedure covers the synthesis and characterization of surface-accessible colloids, the preliminary SERS screening with agglomerated colloids, the synthesis and characterization of interfacial nanoparticle assemblies, termed metal liquid-like films, and the in situ biphasic SERS analysis with metal liquid-like films. The applications of the approach are illustrated using two examples: the probing of π-metal interactions and that of target/ligand-particle interactions on hollow bimetallic nanostars. This protocol, from the initial synthesis of the surface-accessible plasmonic nanoparticles to the final in situ biphasic SERS analysis, requires ~14 h and is ideally suited to users with basic knowledge in performing Raman spectroscopy and wet synthesis of metal nanoparticles.

Preparation of conductive polyaniline hydrogels co‐doped with hydrochloric acid/phytic acid and their application in Ag NPs@PA/GCE biosensor for H2O2 detection

Accurate measurement of hydrogen peroxide is of great significance in monitoring human diseases and environmental safety. At present, there are a variety of testing methods, among which the use of electrochemical sensors to accurately measure hydrogen peroxide has gradually become a research hotspot. In this article, phytic acid (PA) with dual functions of doping and cross‐linking and HCl with strong ionization capacity was introduced as dopants to co‐doping polyaniline, and polyaniline hydrogel with a three‐dimensional network structure was prepared. The influence of the HCl/PA co‐doping ratio on conductive polyaniline hydrogel (CPAniH) was explored. The synthesis process and mechanism of HCl/PA‐CPAniH were analyzed and explained. In addition, the conductivity and mechanism of HCl/PA‐CPAniH, as well as the hydrogel characteristics were characterized and studied. A new electrochemical sensor based on polyaniline hydrogel and silver nanoparticles was constructed to detect hydrogen peroxide. The sensor has a good linear relationship, a wide linear range, and a high‐detection limit for H2O2. In addition, it also shows that HCl/PA‐CPAniH is a good interface material for electrochemical sensors and has a certain application potential.

Cell-Type-Dependent Dissolution of CuO Nanoparticles and Efflux of Cu Ions following Cellular Internalization

CuO nanoparticles (NPs) show promising applications in biosensors, waste treatment, and energy materials, but the growing manufacture of CuO NPs also leads to the concerns for their potential environmental and health risks. However, the cellular fates of CuO NPs such as Cu ion dissolution, transformation, and efflux remain largely speculative. In the present study, we for the first time combined the gold-core labeling and Cu ion bioimaging technologies to reveal the intracellular fates of CuO NPs in different cells following cellular internalization of NPs. We demonstrated that the dissolution rate of CuO NPs depended on the cell type. Following CuO dissolution, limited transformation of Cu(II) to Cu(I) occurred within the cellular microenvironment. Instead, Cu(II) was rapidly eliminated from the cells, and such rapid efflux in different cells was highly dependent on the GSH-mediated pathway and lysosome exocytosis. The labile Cu(I) level in the two cancerous cell lines was immediately regulated upon Cu exposure, which explained their tolerance to Au@CuO NPs. Overall, our study demonstrated a very rapid turnover of Cu in the cells following CuO internalization, which subsequently determined the cellular toxicity of CuO. The results will have important implications for assessing the health risk of CuO NPs.