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

Universitat Rovira i Virgili, Spain
PLoS ONE (Impact Factor: 3.23). 04/2012; 7(4):e35014. DOI: 10.1371/journal.pone.0035014
Source: PubMed


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.

Download full-text


Available from: Robert Damoiseaux
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The production of engineered nanomaterials (ENMs) is a sci-entific breakthrough in material design and the development of new consumer products. While the successful implementation of nanotechnology is important for the growth of the global economy, we also need to consider the possible environmental health and safety (EHS) impact as a result of the novel physicochemical properties that could generate hazardous biological outcomes. In order to assess ENM hazard, reliable and reproducible screening approaches are needed to test the basic materials as well as nanoenabled products. A platform is required to investigate the potentially endless number of biophysicochemical interactions at the nano/bio interface, in response to which we have developed a predictive toxicological approach. We define a predictive toxicological approach as the use of mechanisms-based high-throughput screening in vitro to make predictions about the physicochemical properties of ENMs that may lead to the generation of pathology or disease outcomes in vivo. The in vivo results are used to validate and improve the in vitro high-throughput screening (HTS) and to establish structure-activity relationships (SARs) that allow hazard ranking and modeling by an appropriate combination of in vitro and in vivo testing. This notion is in agreement with the landmark 2007 report from the US National Academy of Sciences, "Toxicity Testing in the 21st Century: A Vision and a Strategy" ( ), which advocates increased efficiency of toxicity testing by transitioning from qualitative, descriptive animal testing to quantitative, mechanistic, and pathway-based toxicity testing in human cells or cell lines using high-throughput approaches. Accordingly, we have implemented HTS approaches to screen compositional and combinatorial ENM libraries to develop hazard ranking and structure-activity relationships that can be used for predicting in vivo injury outcomes. This predictive approach allows the bulk of the screening analysis and high-volume data generation to be carried out in vitro, following which limited, but critical, validation studies are carried out in animals or whole organisms. Risk reduction in the exposed human or environmental populations can then focus on limiting or avoiding exposures that trigger these toxicological responses as well as implementing safer design of potentially hazardous ENMs. In this Account, we review the tools required for establishing predictive toxicology paradigms to assess inhalation and environmental toxicological scenarios through the use of compositional and combinatorial ENM libraries, mechanism-based HTS assays, hazard ranking, and development of nano-SARs. We will discuss the major injury paradigms that have emerged based on specific ENM properties, as well as describing the safer design of ZnO nanoparticles based on characterization of dissolution chemistry as a major predictor of toxicity.
    Full-text · Article · Jun 2012 · Accounts of Chemical Research
  • [Show abstract] [Hide abstract]
    ABSTRACT: Due to several inherent advantages, zebrafish are being utilized in increasingly sophisticated screens to assess the physiological effects of chemical compounds directly in living vertebrate organisms. Diverse screening platforms showcase these advantages. Morphological assays encompassing basic qualitative observations to automated imaging, manipulation, and data-processing systems provide whole organism to subcellular levels of detail. Behavioral screens extend chemical screening to the level of complex systems. In addition, zebrafish-based disease models provide a means of identifying new potential therapeutic strategies. Automated systems for handling/sorting, high-resolution imaging and quantitative data collection have significantly increased throughput in recent years. These advances will make it easier to capture multiple streams of information from a given sample and facilitate integration of zebrafish at the earliest stages of the drug-discovery process, providing potential solutions to current drug-development bottlenecks. Here we outline advances that have been made within the growing field of zebrafish chemical screening.
    No preview · Article · Sep 2012 · Future medicinal chemistry
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The rising production of nanomaterial-based consumer products has raised safety concerns. Testing these with animal and other direct models is neither ethically nor economically viable, nor quick enough. This review aims to discuss the strength of in vitro testing, including the use of 2D and 3D cultures, stem cells, and tissue constructs, etc., which would give fast and repeatable answers of a highly specific nature, while remaining relevant to in vivo outcomes. These results can then be combined and the overall toxicity predicted with relative accuracy. Such in vitro models can screen potentially toxic nanomaterials which, if required, can undergo further stringent studies in animals. The cyto- and phototoxicity of some high-volume production nanomaterials, using in vitro models, is also reviewed.
    Full-text · Article · May 2013 · Small
Show more