Genomics

Dataset Information

0

Development of a neural rosette formation assay (RoFA) to identify neurodevelopmental toxicants and to characterize their transcriptome disturbances


ABSTRACT: The first in vitro tests for developmental toxicity made use of rodent cells. Newer teratology tests, e.g. developed during the ESNATS project, use human cells and measure mechanistic endpoints (such as transcriptome changes). However, the toxicological implications of mechanistic parameters are hard to judge, without functional/morphological endpoints. To address this issue, we developed a new version of the human stem cell-based test STOP-tox(UKN). For this purpose, the capacity of the cells to self-organize to neural rosettes was assessed as functional endpoint: pluripotent stem cells were allowed to differentiate to neuroepithelial cells for six days in the presence or absence of toxicants. Then, both transcriptome changes were measured (standard STOP-tox(UKN)), and cells were allowed to form rosettes. After optimization of staining methods, an imaging algorithm for rosette quantification was implemented and used for an automated rosette formation assay (RoFA). Neural tube toxicants (like valproic acid), which are known to disturb human development at stages when rosette-forming cells are present, were used as positive controls. Established toxicants led to distinctly different tissue organization and differentiation stages. RoFA outcome and transcript changes largely correlated concerning (i) the concentration-dependence, (ii) the time-dependence, and (iii) the set of positive hits identified amongst 24 potential toxicants. Using such comparative data, a prediction model for the RoFA was developed. The comparative analysis was also used to identify gene dysregulations that are particularly predictive for disturbed rosette formation. This ‘RoFA predictor gene set’ may be used for a simplified and less costly setup of the STOP-tox(UKN) assay.

ORGANISM(S): Homo sapiens

PROVIDER: GSE141253 | GEO | 2019/12/03

REPOSITORIES: GEO

Similar Datasets

2023-04-19 | GSE229567 | GEO
2013-08-08 | E-GEOD-40010 | biostudies-arrayexpress
2023-07-03 | GSE218703 | GEO
2013-08-08 | GSE40010 | GEO
2023-07-03 | GSE227013 | GEO
2020-02-15 | GSE144503 | GEO
2017-07-24 | GSE83861 | GEO
2012-12-21 | GSE41463 | GEO
2008-10-25 | E-GEOD-9956 | biostudies-arrayexpress
2012-12-21 | E-GEOD-41463 | biostudies-arrayexpress