Omnisphero: a high-content image analysis (HCA) approach for phenotypic developmental neurotoxicity (DNT) screenings of organoid neurosphere cultures in vitro

• Published in: Archives of toxicology Vol. 91; no. 4; pp. 2017 - 2028
• Main Authors: Schmuck, Martin R., Temme, Thomas, Dach, Katharina, de Boer, Denise, Barenys, Marta, Bendt, Farina, Mosig, Axel, Fritsche, Ellen
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-04-2017; Springer Nature B.V
• Subjects: Analysis; Animal Testing Alternatives; Biomedical and Life Sciences; Biomedicine; Cell adhesion & migration; Cell Culture Techniques; Cell Differentiation - drug effects; Cell Movement - drug effects; Cells, Cultured; Environmental Health; Genotype & phenotype; Humans; Imaging, Three-Dimensional - methods; Neural Stem Cells - drug effects; Neural Stem Cells - pathology; Neurotoxicity; Neurotoxicity Syndromes - etiology; Occupational Medicine/Industrial Medicine; Organoids - drug effects; Organoids - pathology; Pharmacology/Toxicology; Protocols; Toxicity Tests - methods; Neuronal identification; Developmental neurotoxicity (DNT); Migration; Neurite outgrowth; Neurospheres; High-content image analysis (HCA)
• DOI: 10.1007/s00204-016-1852-2
• EISSN: 1432-0738
• ISSN: 0340-5761

Current developmental neurotoxicity (DNT) testing in animals faces major limitations, such as high cost and time demands as well as uncertainties in their methodology, evaluation and regulation. Therefore, the use of human-based 3D in vitro systems in combination with high-content image analysis (HCA) might contribute to DNT testing with lower costs, increased throughput and enhanced predictivity for human hazard identification. Human neural progenitor cells (hNPCs) grown as 3D neurospheres mimic basic processes of brain development including hNPC migration and differentiation and are therefore useful for DNT hazard identification. HCA of migrated neurospheres creates new challenges for automated evaluations because it encompasses variable cell densities, inconsistent
z
-layers and heterogeneous cell populations. We tackle those challenges with our
Omnisphero
software, which assesses multiple endpoints of the ‘Neurosphere Assay.’ For neuronal identification,
Omnisphero
reaches a true positive rate (TPR) of 83.8 % and a false discovery rate (FDR) of 11.4 %, thus being comparable to the interindividual difference among two researchers (TPR = 94.3, FDR = 11.0 %) and largely improving the results obtained by an existing HCA approach, whose TPR does not exceed 50 % at a FDR above 50 %. The high FDR of existing methods results in incorrect measurements of neuronal morphological features accompanied by an overestimation of compound effects.
Omnisphero
additionally includes novel algorithms to assess ‘neurosphere-specific’ endpoints like radial migration and neuronal density distribution within the migration area. Furthermore, a user-assisted parameter optimization procedure makes
Omnisphero
accessible to non-expert end users.