Studying nanotoxic effects of CdTe quantum dots in Trypanosoma cruzi

Semiconductor nanoparticles, such as quantum dots (QDs), were used to carry out experiments in vivo and ex vivo with Trypanosoma cruzi. However, questions have been raised regarding the nanotoxicity of QDs in living cells, microorganisms, tissues and whole animals. The objective of this paper was to conduct a QD nanotoxicity study on living T. cruzi protozoa using analytical methods. This was accomplished using in vitro experiments to test the interference of the QDs on parasite development, morphology and viability. Our results show that after 72 h, a 200 μM cadmium telluride (CdTe) QD solution induced important morphological alterations in T. cruzi, such as DNA damage, plasma membrane blebbing and mitochondrial swelling. Flow cytometry assays showed no damage to the plasma membrane when incubated with 200 μM CdTe QDs for up to 72 h (propidium iodide cells), giving no evidence of classical necrosis. Parasites incubated with 2 μM CdTe QDs still proliferated after seven days. In summary, a low concentration of CdTe QDs (2 μM) is optimal for bioimaging, whereas a high concentration (200 μM CdTe) could be toxic to cells. Taken together, our data indicate that 2 μM QD can be used for the successful long-term study of the parasite-vector interaction in real time

Automated Phenotype Recognition for Zebrafish Embryo Based In Vivo High Throughput Toxicity Screening of Engineered Nano-Materials

A phenotype recognition model was developed for high throughput screening (HTS) of engineered Nano-Materials (eNMs) toxicity using zebrafish embryo developmental response classified, from automatically captured images and without manual manipulation of zebrafish positioning, by three basic phenotypes (i.e., hatched, unhatched, and dead). The recognition model was built with a set of vectorial descriptors providing image color and texture information. The best performing model was attained with three image descriptors (color histogram, representative color, and color layout) identified as most suitable from an initial pool of six descriptors. This model had an average recognition accuracy of 97.40±0.95% in a 10-fold cross-validation and 93.75% in a stress test of low quality zebrafish images. The present work has shown that a phenotyping model can be developed with accurate recognition ability suitable for zebrafish-based HTS assays. Although the present methodology was successfully demonstrated for only three basic zebrafish embryonic phenotypes, it can be readily adapted to incorporate more subtle phenotypes