An in vivo study of nanorod, nanosphere, and nanowire forms of titanium dioxide using Drosophila melanogaster: toxicity, cellular uptake, oxidative stress, and DNA damage.
Eşref DemirPublished in: Journal of toxicology and environmental health. Part A (2020)
The biological impact of nanomaterials (NMs) is determined by several factors such as size and shape, which need to be taken into consideration in any type of analysis. While investigators often prefer to conduct in vitro studies for detection of any possible adverse effects of NMs, in vivo approaches yield more relevant data for risk assessment. For this reason, Drosophila melanogaster was selected as a suitable in vivo model to characterize the potential risks associated with exposure nanorods (NRs), nanospheres (NSs), nanowires (NWs) forms of titanium dioxide (TiO2), and their microparticulated (or bulk) form, as TiO2. Third instar larvae (72 hr old larvae) were fed with TiO2 (NRs, NSs, or NWs) and TiO2 at concentrations ranging from 0.01 to 10 mM. Viability (toxicity), internalization (cellular uptake), intracellular reactive oxygen species (ROS) production, and genotoxicity (Comet assay) were the end-points evaluated in hemocyte D. melanogaster larvae. Significant intracellular oxidative stress and genotoxicity were noted at the highest exposure concentration (10 mM) of TiO2 (NRs, NSs, or NWs), as determined by the Comet assay and ROS analysis, respectively. A concentration-effect relationship was observed in hemocytes exposed to the NMs. Data demonstrated that selected forms of TiO2.-induced genotoxicity in D. melanogaster larvae hemocytes indicating this organism is susceptible for use as a model to examine in vivo NMs-mediated effects.
Keyphrases
- drosophila melanogaster
- oxidative stress
- dna damage
- reactive oxygen species
- quantum dots
- visible light
- diabetic rats
- risk assessment
- human health
- high throughput
- cell death
- oxide nanoparticles
- aedes aegypti
- room temperature
- drug induced
- signaling pathway
- big data
- climate change
- label free
- gold nanoparticles
- data analysis
- endothelial cells
- deep learning