PUBLICATION

Automated phenotype recognition for zebrafish embryo based in vivo high throughput toxicity screening of engineered nano-materials

Authors
Liu, R., Lin, S., Rallo, R., Zhao, Y., Damoiseaux, R., Xia, T., Lin, S., Nel, A., and Cohen, Y.
ID
ZDB-PUB-120417-10
Date
2012
Source
PLoS One   7(4): e35014 (Journal)
Registered Authors
Zhao, Yan
Keywords
none
MeSH Terms
  • Animals
  • Embryo, Nonmammalian/drug effects
  • High-Throughput Screening Assays/methods*
  • Image Processing, Computer-Assisted/methods*
  • Models, Biological
  • Nanostructures/analysis*
  • Nanostructures/toxicity*
  • Phenotype
  • Toxicity Tests/methods*
  • Zebrafish/embryology*
PubMed
22506062 Full text @ PLoS One
Abstract

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.

Genes / Markers
Figures
Show all Figures
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping