Stacey L. Harper

Fullerene C60 exposure elicits an oxidative stress response in embryonic zebrafish.

Due to its unique physicochemical and optical properties, C60 has raised interest in commercialization for a variety of products. While several reports have determined this nanomaterial to act as a powerful antioxidant, many other studies have demonstrated a strong oxidative potential through photoactivation. To directly address the oxidative potential of C60, the effects of light and chemical supplementation and depletion of glutathione (GSH) on C60-induced toxicity were evaluated. Embryonic zebrafish were used as a model organism to examine the potential of C60 to elicit oxidative stress responses. Reduced light during C60 exposure significantly decreased mortality and the incidence of fin malformations and pericardial edema at 200 and 300 ppb C60. Embryos co-exposed to the glutathione precursor, N-acetylcysteine (NAC), also showed reduced mortality and pericardial edema; however, fin malformations were not reduced. Conversely, co-exposure to the GSH synthesis inhibitors, buthionine sulfoximine (BSO) and diethyl maleate (DEM), increased the sensitivity of zebrafish to C60 exposure. Co-exposure of C60 or its hydroxylated derivative, C60(OH)(24), with H2O2 resulted in increased mortality along the concentration gradient of H2O2 for both materials. Microarrays were used to examine the effects of C60 on the global gene expression at two time points, 36 and 48 h post fertilization (hpf). At both life stages there were alterations in the expression of several key stress response genes including glutathione-S-transferase, glutamate cysteine ligase, ferritin, alpha-tocopherol transport protein and heat shock protein 70. These results support the hypothesis that C60 induces oxidative stress in this model system.

Systematic Evaluation of Nanomaterial Toxicity: Utility of Standardized Materials and Rapid Assays

The challenge of optimizing both performance and safety in nanomaterials hinges on our ability to resolve which structural features lead to desired properties. It has been difficult to draw meaningful conclusions about biological impacts from many studies of nanomaterials due to the lack of nanomaterial characterization, unknown purity, and/or alteration of the nanomaterials by the biological environment. To investigate the relative influence of core size, surface chemistry, and charge on nanomaterial toxicity, we tested the biological response of whole animals exposed to a matrix of nine structurally diverse, precision-engineered gold nanoparticles (AuNPs) of high purity and known composition. Members of the matrix include three core sizes and four unique surface coatings that include positively and negatively charged headgroups. Mortality, malformations, uptake, and elimination of AuNPs were all dependent on these parameters, showing the need for tightly controlled experimental design and nanomaterial characterization. Results presented herein illustrate the value of an integrated approach to identify design rules that minimize potential hazard.

Evaluation of embryotoxicity using the zebrafish model

The embryonic zebrafish model offers the power of whole-animal investigations (e.g., intact organism, functional homeostatic feedback mechanisms, and intercellular signaling) with the convenience of cell culture (e.g., cost- and time-efficient, minimal infrastructure, small quantities of nanomaterial solutions required). The model system overcomes many of the current limitations in rapid to high-throughput screening of drugs/compounds and casts a broad net to evaluate integrated system effects rapidly. Additionally, it is an ideal platform to follow up with targeted studies aimed at the mechanisms of toxic action. Exposures are carried out in 96-well plates so minimal solution volumes are required for the assessments. Numerous morphological, developmental, and behavioral endpoints can be evaluated noninvasively due to the transparent nature of the embryos.

In vivo biodistribution and toxicity depends on nanomaterial composition, size, surface functionalisation and route of exposure

Anticipated growth of the nanotechnology industry has motivated the development of rapid, relevant and efficient testing strategies to evaluate the biological activity and toxic potential of the growing number of novel nanoparticles. Since nanoparticles may interact with biological systems in unforeseen ways, it is important that evaluation of nanomaterial–biological interactions cover a broad range of cell types, tissues, organs and systems. Here, we use the embryonic zebrafish as a dynamic whole animal (in vivo) assay to investigate the importance of chemical composition, size, surface functionalisation and route of exposure on nanomaterial–biological interactions and delineate nanomaterials that are biologically active from those that are not. Information gained using model systems, such as the embryonic zebrafish, can be used to direct the rational development of safer, less hazardous nanoparticles. Our results demonstrate the utility of this model as an effective and accurate tool to assess the biological activity and toxic potential of nanomaterials in a short period of time with minimal cost.

ISA-TAB-Nano: A Specification for Sharing Nanomaterial Research Data in Spreadsheet-based Format

Background and motivationThe high-throughput genomics communities have been successfully using standardized spreadsheet-based formats to capture and share data within labs and among public repositories. The nanomedicine community has yet to adopt similar standards to share the diverse and multi-dimensional types of data (including metadata) pertaining to the description and characterization of nanomaterials. Owing to the lack of standardization in representing and sharing nanomaterial data, most of the data currently shared via publications and data resources are incomplete, poorly-integrated, and not suitable for meaningful interpretation and re-use of the data. Specifically, in its current state, data cannot be effectively utilized for the development of predictive models that will inform the rational design of nanomaterials.ResultsWe have developed a specification called ISA-TAB-Nano, which comprises four spreadsheet-based file formats for representing and integrating various types of nanomaterial data. Three file formats (Investigation, Study, and Assay files) have been adapted from the established ISA-TAB specification; while the Material file format was developed de novo to more readily describe the complexity of nanomaterials and associated small molecules. In this paper, we have discussed the main features of each file format and how to use them for sharing nanomaterial descriptions and assay metadata.ConclusionThe ISA-TAB-Nano file formats provide a general and flexible framework to record and integrate nanomaterial descriptions, assay data (metadata and endpoint measurements) and protocol information. Like ISA-TAB, ISA-TAB-Nano supports the use of ontology terms to promote standardized descriptions and to facilitate search and integration of the data. The ISA-TAB-Nano specification has been submitted as an ASTM work item to obtain community feedback and to provide a nanotechnology data-sharing standard for public development and adoption.

Informatics and Standards for Nanomedicine Technology

There are several issues to be addressed concerning the management and effective use of information (or data), generated from nanotechnology studies in biomedical research and medicine. These data are large in volume, diverse in content, and are beset with gaps and ambiguities in the description and characterization of nanomaterials. In this work, we have reviewed three areas of nanomedicine informatics: information resources; taxonomies, controlled vocabularies, and ontologies; and information standards. Informatics methods and standards in each of these areas are critical for enabling collaboration; data sharing; unambiguous representation and interpretation of data; semantic (meaningful) search and integration of data; and for ensuring data quality, reliability, and reproducibility. In particular, we have considered four types of information standards in this article, which are standard characterization protocols, common terminology standards, minimum information standards, and standard data communication (exchange) formats. Currently, because of gaps and ambiguities in the data, it is also difficult to apply computational methods and machine learning techniques to analyze, interpret, and recognize patterns in data that are high dimensional in nature, and also to relate variations in nanomaterial properties to variations in their chemical composition, synthesis, characterization protocols, and so on. Progress toward resolving the issues of information management in nanomedicine using informatics methods and standards discussed in this article will be essential to the rapidly growing field of nanomedicine informatics.

Proactively designing nanomaterials to enhance performance and minimise hazard

The innovative field of nanotechnology is most likely to benefit society and gain acceptance if environmental and human health considerations are investigated systematically, and those results are used to optimise safety as well as performance. Since nanotechnology fundamentally allows manipulation of matter at the atomic level, toxic interactions could potentially be eliminated by creative design once our knowledge of how nanomaterials interact with biological systems is sufficient. Our approach to the development of benign nanoparticles begins with the synthesis of precisely engineered, high-purity nanoparticle libraries using the principles of green chemistry. Next, evaluations for biocompatibility are performed using a rapid in vivo system (embryonic zebrafish) to assess the biological activity and toxic potential of nanomaterials at multiple levels of biological organisation (i.e., molecular, cellular, systems, organismal). Our iterative testing and redesign strategy utilises information gained from the biological studies to inform the nanomaterial design process until benign products and processes are identified. To make this information more generally available, a knowledgebase of Nanomaterial-Biological Interactions (NBI) is being developed that will offer industry, academia and regulatory agencies a mechanism to rationally inquire for unbiased interpretation of nanomaterial exposure effects in biological systems. Timely evaluation and dissemination of information on nanomaterial-biological interactions will provide much needed data, improve public trust of the nanotechnology industry, and provide nanomaterial designers in academia and industry with information to direct the development of safer nanomaterials and resulting technologies.

Predictive modeling of nanomaterial exposure effects in biological systems

Background Predictive modeling of the biological effects of nanomaterials is critical for industry and policymakers to assess the potential hazards resulting from the application of engineered nanomaterials. Methods We generated an experimental dataset on the toxic effects experienced by embryonic zebrafish due to exposure to nanomaterials. Several nanomaterials were studied, such as metal nanoparticles, dendrimer, metal oxide, and polymeric materials. The embryonic zebrafish metric (EZ Metric) was used as a screening-level measurement representative of adverse effects. Using the dataset, we developed a data mining approach to model the toxic endpoints and the overall biological impact of nanomaterials. Data mining techniques, such as numerical prediction, can assist analysts in developing risk assessment models for nanomaterials. Results We found several important attributes that contribute to the 24 hours post-fertilization (hpf) mortality, such as dosage concentration, shell composition, and surface charge. These findings concur with previous studies on nanomaterial toxicity using embryonic zebrafish. We conducted case studies on modeling the overall effect/impact of nanomaterials and the specific toxic endpoints such as mortality, delayed development, and morphological malformations. The results show that we can achieve high prediction accuracy for certain biological effects, such as 24 hpf mortality, 120 hpf mortality, and 120 hpf heart malformation. The results also show that the weighting scheme for individual biological effects has a significant influence on modeling the overall impact of nanomaterials. Sample prediction models can be found at http://neiminer.i-a-i.com/nei_models. Conclusion The EZ Metric-based data mining approach has been shown to have predictive power. The results provide valuable insights into the modeling and understanding of nanomaterial exposure effects.

The Impact of Surface Ligands and Synthesis Method on the Toxicity of Glutathione-Coated Gold Nanoparticles

Gold nanoparticles (AuNPs) are increasingly used in biomedical applications, hence understanding the processes that affect their biocompatibility and stability are of significant interest. In this study, we assessed the stability of peptide-capped AuNPs and used the embryonic zebrafish (Danio rerio) as a vertebrate system to investigate the impact of synthesis method and purity on their biocompatibility. Using glutathione (GSH) as a stabilizer, Au-GSH nanoparticles with identical core sizes were terminally modified with Tryptophan (Trp), Histidine (His) or Methionine (Met) amino acids and purified by either dialysis or ultracentrifugation. Au-GSH-(Trp)₂ purified by dialysis elicited significant morbidity and mortality at 200 µg/mL, Au-GSH-(His)₂ induced morbidity and mortality after purification by either method at 20 and 200 µg/mL, and Au-GSH-(Met)₂ caused only sublethal responses at 200 µg/mL. Overall, toxicity was significantly reduced and ligand structure was improved by implementing ultracentrifugation purifications at several stages during the multi-step synthesis and surface modification of Au-GSH nanoparticles. When carefully synthesized at high purity, peptide-functionalized AuNPs showed high biocompatibility in biological systems.Gold nanoparticles (AuNPs) are increasingly used in biomedical applications, hence understanding the processes that affect their biocompatibility and stability are of significant interest. In this study, we assessed the stability of peptide-capped AuNPs and used the embryonic zebrafish (Danio rerio) as a vertebrate system to investigate the impact of synthesis method and purity on their biocompatibility. Using glutathione (GSH) as a stabilizer, Au-GSH nanoparticles with identical core sizes were terminally modified with Tryptophan (Trp), Histidine (His) or Methionine (Met) amino acids and purified by either dialysis or ultracentrifugation. Au-GSH-(Trp)2 purified by dialysis elicited significant morbidity and mortality at 200 µg/mL, Au-GSH-(His)2 induced morbidity and mortality after purification by either method at 20 and 200 µg/mL, and Au-GSH-(Met)2 caused only sublethal responses at 200 µg/mL. Overall, toxicity was significantly reduced and ligand structure was improved by implementing ultracentrifugation purifications at several stages during the multi-step synthesis and surface modification of Au-GSH nanoparticles. When carefully synthesized at high purity, peptide-functionalized AuNPs showed high biocompatibility in biological systems.

NEIMiner: nanomaterial environmental impact data miner

As more engineered nanomaterials (eNM) are developed for a wide range of applications, it is crucial to minimize any unintended environmental impacts resulting from the application of eNM. To realize this vision, industry and policymakers must base risk management decisions on sound scientific information about the environmental fate of eNM, their availability to receptor organisms (eg, uptake), and any resultant biological effects (eg, toxicity). To address this critical need, we developed a model-driven, data mining system called NEIMiner, to study nanomaterial environmental impact (NEI). NEIMiner consists of four components: NEI modeling framework, data integration, data management and access, and model building. The NEI modeling framework defines the scope of NEI modeling and the strategy of integrating NEI models to form a layered, comprehensive predictability. The data integration layer brings together heterogeneous data sources related to NEI via automatic web services and web scraping technologies. The data management and access layer reuses and extends a popular content management system (CMS), Drupal, and consists of modules that model the complex data structure for NEI-related bibliography and characterization data. The model building layer provides an advanced analysis capability for NEI data. Together, these components provide significant value to the process of aggregating and analyzing large-scale distributed NEI data. A prototype of the NEIMiner system is available at http://neiminer.i-a-i.com/.