Skip to main content

Combination of multiple neural crest migration assays to identify environmental toxicants from a proof-of-concept chemical library


Many in vitro tests have been developed to screen for potential neurotoxicity. However, only few cell function-based tests have been used for comparative screening, and thus experience is scarce on how to confirm and evaluate screening hits. We addressed these questions for the neural crest cell migration test (cMINC). After an initial screen, a hit follow-up strategy was devised. A library of 75 compounds plus internal controls (NTP80-list), assembled by the National Toxicology Program of the USA (NTP) was used. It contained some known classes of (developmental) neurotoxic compounds. The primary screen yielded 23 confirmed hits, which comprised ten flame retardants, seven pesticides and six drug-like compounds. Comparison of concentration–response curves for migration and viability showed that all hits were specific. The extent to which migration was inhibited was 25–90%, and two organochlorine pesticides (DDT, heptachlor) were most efficient. In the second part of this study, (1) the cMINC assay was repeated under conditions that prevent proliferation; (2) a transwell migration assay was used as a different type of migration assay; (3) cells were traced to assess cell speed. Some toxicants had largely varying effects between assays, but each hit was confirmed in at least one additional test. This comparative study allows an estimate on how confidently the primary hits from a cell function-based screen can be considered as toxicants disturbing a key neurodevelopmental process. Testing of the NTP80-list in more assays will be highly interesting to assemble a test battery and to build prediction models for developmental toxicity.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9



Adverse outcome pathways


Cytosine arabinoside


Circular MINC


Cytochalasin D


Dimethyl sulfoxide


Developmental neurotoxicity


Effective concentration


EC90 of viability


EC75 of migration


Epigallocatechin gallate


Epidermal growth factor


Foetal bovine serum


Fibroblast growth factor


Flame retardant


Grid-independent descriptors


Human embryonic stem cell

logP :

Octanol–water distribution coefficient


Methylmercury(II) chloride


Migration of neural crest cell


Molecular weight


Neural crest cell


Number of hydrogen bond acceptors


No observed adverse effect level for viability


Number of rotatable bonds


National Toxicology Program


Polycyclic aromatic hydrocarbon


Polybrominated diphenyl ether


Phosphate buffered saline


Principal component analysis


Quantitative structure-activity relationship


Region of interest


Tetrabromobisphenol A


Polar surface


  1. Adler S et al (2011) Alternative (non-animal) methods for cosmetics testing: current status and future prospects-2010. Arch Toxicol 85:367–485. doi:10.1007/s00204-011-0693-2

    CAS  Article  PubMed  Google Scholar 

  2. Aschner M et al (2016) Reference compounds for alternative test methods to indicate developmental neurotoxicity (DNT) potential of chemicals: example lists and criteria for their selection and use. Altex. doi:10.14573/altex.1604201

    PubMed  PubMed Central  Google Scholar 

  3. Bal-Price AK et al (2012) Advancing the science of developmental neurotoxicity (DNT): testing for better safety evaluation. Altex 29:202–215

    Article  PubMed  Google Scholar 

  4. Bal-Price A et al (2015) International STakeholder NETwork (ISTNET): creating a developmental neurotoxicity (DNT) testing road map for regulatory purposes. Arch Toxicol 89:269–287. doi:10.1007/s00204-015-1464-2

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  5. Barenys M et al (2016) Epigallocatechin gallate (EGCG) inhibits adhesion and migration of neural progenitor cells in vitro. Arch Toxicol. doi:10.1007/s00204-016-1709-8

    Google Scholar 

  6. Basketter DA, White IR, McFadden JP, Kimber I (2015) Skin sensitization: implications for integration of clinical data into hazard identification and risk assessment. Hum Exp Toxicol 34:1222–1230. doi:10.1177/0960327115601760

    CAS  Article  PubMed  Google Scholar 

  7. Behl M et al (2016) Editor’s highlight: Comparative Toxicity of Organophosphate Flame Retardants and Polybrominated Diphenyl Ethers to Caenorhabditis elegans. Toxicol Sci 154:241–252. doi:10.1093/toxsci/kfw162

    CAS  Article  PubMed  Google Scholar 

  8. Browne P, Judson RS, Casey WM, Kleinstreuer NC, Thomas RS (2015) Screening chemicals for estrogen receptor bioactivity using a computational model. Environ Sci Technol 49:8804–8814. doi:10.1021/acs.est.5b02641

    CAS  Article  PubMed  Google Scholar 

  9. Colaianna M et al (2016) Fingerprinting of neurotoxic compounds using a mouse embryonic stem cell dual luminescence reporter assay. Arch Toxicol. doi:10.1007/s00204-016-1690-2

    PubMed  PubMed Central  Google Scholar 

  10. Collins FS, Gray GM, Bucher JR (2008) Toxicology. Transforming environmental health protection. Science 319:906–907. doi:10.1126/science.1154619

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. Combes R, Grindon C, Cronin MT, Roberts DW, Garrod JF (2008) Integrated decision-tree testing strategies for mutagenicity and carcinogenicity with respect to the requirements of the EU REACH legislation. Altern Lab Anim 36(Suppl 1):43–63

    CAS  PubMed  Google Scholar 

  12. Crofton KM et al (2011) Developmental neurotoxicity testing: recommendations for developing alternative methods for the screening and prioritization of chemicals. Altex 28:9–15

    PubMed  Google Scholar 

  13. Crofton KM, Mundy WR, Shafer TJ (2012) Developmental neurotoxicity testing: a path forward. Congenit Anom (Kyoto) 52:140–146. doi:10.1111/j.1741-4520.2012.00377.x

    Article  Google Scholar 

  14. Dreser N et al (2015) Grouping of histone deacetylase inhibitors and other toxicants disturbing neural crest migration by transcriptional profiling. Neurotoxicology 50:56–70. doi:10.1016/j.neuro.2015.07.008

    CAS  Article  PubMed  Google Scholar 

  15. Duran A, Zamora I, Pastor M (2009) Suitability of GRIND-based principal properties for the description of molecular similarity and ligand-based virtual screening. J Chem Inf Model 49:2129–2138. doi:10.1021/ci900228x

    CAS  Article  PubMed  Google Scholar 

  16. Ezendam J, Braakhuis HM, Vandebriel RJ (2016) State of the art in non-animal approaches for skin sensitization testing: from individual test methods towards testing strategies. Arch Toxicol 90:2861–2883. doi:10.1007/s00204-016-1842-4

    CAS  Article  PubMed  Google Scholar 

  17. Fritsche E, Cline JE, Nguyen N-H, Scanlan TS, Abel J (2005) Polychlorinated biphenyls disturb differentiation of normal human neural progenitor cells: clue for involvement of thyroid hormone receptors. Environ Health Perspect 113:871–876. doi:10.1289/ehp.7793

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  18. Grinberg M et al (2014) Toxicogenomics directory of chemically exposed human hepatocytes. Arch Toxicol 88:2261–2287. doi:10.1007/s00204-014-1400-x

    CAS  Article  PubMed  Google Scholar 

  19. Hartung T (2016) Making big sense from big data in toxicology by read-across. Altex 33:83–93. doi:10.14573/altex.1603091

    Article  PubMed  Google Scholar 

  20. Hirsch C et al (2016) Multiparameter toxicity assessment of novel DOPO-derived organophosphorus flame retardants. Arch Toxicol. doi:10.1007/s00204-016-1680-4

    PubMed  PubMed Central  Google Scholar 

  21. Hoelting L et al (2016) Stem cell-derived immature human dorsal root ganglia neurons to identify peripheral neurotoxicants. Stem Cells Transl Med 5:476–487. doi:10.5966/sctm.2015-0108

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  22. Huang R et al (2016) Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization. Nat Commun 7:10425. doi:10.1038/ncomms10425

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  23. Igarashi Y, Nakatsu N, Yamashita T, Ono A, Ohno Y, Urushidani T, Yamada H (2015) Open TG-GATEs: a large-scale toxicogenomics database. Nucleic Acids Res 43:D921–D927. doi:10.1093/nar/gku955

    CAS  Article  PubMed  Google Scholar 

  24. Jaworska JS, Natsch A, Ryan C, Strickland J, Ashikaga T, Miyazawa M (2015) Bayesian integrated testing strategy (ITS) for skin sensitization potency assessment: a decision support system for quantitative weight of evidence and adaptive testing strategy. Arch Toxicol 89:2355–2383. doi:10.1007/s00204-015-1634-2

    CAS  Article  PubMed  Google Scholar 

  25. Juberg DR et al (2016) FutureTox III: bridges for translation. Toxicol Sci. doi:10.1093/toxsci/kfw194

    PubMed  Google Scholar 

  26. Judson R et al (2013) Perspectives on validation of high-throughput assays supporting 21st century toxicity testing. Altex 30:51–56

    Article  PubMed  PubMed Central  Google Scholar 

  27. Judson R et al (2014) In vitro and modelling approaches to risk assessment from the U.S. Environmental Protection Agency ToxCast programme. Basic Clin Pharmacol Toxicol 115:69–76. doi:10.1111/bcpt.12239

    CAS  Article  PubMed  Google Scholar 

  28. Judson R et al (2016) Analysis of the effects of cell stress and cytotoxicity on in vitro assay activity across a diverse chemical and assay space. Toxicol Sci 153:409. doi:10.1093/toxsci/kfw148

    CAS  Article  PubMed  Google Scholar 

  29. Kaneko N, Sawada M, Sawamoto K (2017) Mechanisms of neuronal migration in the adult brain. J Neurochem. doi:10.1111/jnc.14002

    Google Scholar 

  30. Kim IJ, Beck HN, Lein PJ, Higgins D (2002) Interferon gamma induces retrograde dendritic retraction and inhibits synapse formation. J Neurosci 22(11):4530–4539

    CAS  PubMed  Google Scholar 

  31. Kroese ED et al (2015) Evaluation of an alternative in vitro test battery for detecting reproductive toxicants in a grouping context. Reprod Toxicol 55:11–19. doi:10.1016/j.reprotox.2014.10.003

    CAS  Article  PubMed  Google Scholar 

  32. Krug AK, Balmer NV, Matt F, Schonenberger F, Merhof D, Leist M (2013) Evaluation of a human neurite growth assay as specific screen for developmental neurotoxicants. Arch Toxicol 87:2215–2231. doi:10.1007/s00204-013-1072-y

    CAS  Article  PubMed  Google Scholar 

  33. Leist M, Hartung T, Nicotera P (2008) The dawning of a new age of toxicology. Altex 25:103–114

    Article  PubMed  Google Scholar 

  34. Leist M, Efremova L, Karreman C (2010) Food for thought … considerations and guidelines for basic test method descriptions in toxicology. Altex 27:309–317

    Article  PubMed  Google Scholar 

  35. Leist M et al (2014) Consensus report on the future of animal-free systemic toxicity testing. Altex 31:341–356. doi:10.14573/altex.1406091

    PubMed  Google Scholar 

  36. Linares V, Belles M, Domingo JL (2015) Human exposure to PBDE and critical evaluation of health hazards. Arch Toxicol 89:335–356. doi:10.1007/s00204-015-1457-1

    CAS  Article  PubMed  Google Scholar 

  37. Luhmann HJ, Fukuda A, Kilb W (2015) Control of cortical neuronal migration by glutamate and GABA. Front Cell Neurosci 9:4. doi:10.3389/fncel.2015.00004

    Article  PubMed  PubMed Central  Google Scholar 

  38. Milletti F, Storchi L, Sforna G, Cruciani G (2007) New and original pKa prediction method using grid molecular interaction fields. J Chem Inf Model 47:2172–2181. doi:10.1021/ci700018y

    CAS  Article  PubMed  Google Scholar 

  39. Moors M et al (2009) Human neurospheres as three-dimensional cellular systems for developmental neurotoxicity testing. Environ Health Perspect 117:1131–1138. doi:10.1289/ehp.0800207

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  40. Nyffeler J, Karreman C, Leisner H, Kim YJ, Lee G, Waldmann T, Leist M (2016) Design of a high-throughput human neural crest cell migration assay to indicate potential developmental toxicants. Altex. doi:10.14573/altex.1605031

    PubMed  Google Scholar 

  41. Pallocca G et al (2016) Identification of transcriptome signatures and biomarkers specific for potential developmental toxicants inhibiting human neural crest cell migration. Arch Toxicol 90:159–180. doi:10.1007/s00204-015-1658-7

    CAS  Article  PubMed  Google Scholar 

  42. Pastor M, Cruciani G, McLay I, Pickett S, Clementi S (2000) GRid-INdependent descriptors (GRIND): a novel class of alignment-independent three-dimensional molecular descriptors. J Med Chem 43:3233–3243

    CAS  Article  PubMed  Google Scholar 

  43. Patlewicz G, Fitzpatrick JM (2016) Current and future perspectives on the development, evaluation, and application of in silico approaches for predicting toxicity. Chem Res Toxicol 29:438–451. doi:10.1021/acs.chemrestox.5b00388

    CAS  Article  PubMed  Google Scholar 

  44. Pei Y et al (2015) Comparative neurotoxicity screening in human iPSC-derived neural stem cells, neurons and astrocytes. Brain Res. doi:10.1016/j.brainres.2015.07.048

    PubMed Central  Google Scholar 

  45. Piersma AH et al (2013) Evaluation of an alternative in vitro test battery for detecting reproductive toxicants. Reprod Toxicol 38:53–64. doi:10.1016/j.reprotox.2013.03.002

    CAS  Article  PubMed  Google Scholar 

  46. R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

    Google Scholar 

  47. Reisinger K et al (2015) Systematic evaluation of non-animal test methods for skin sensitisation safety assessment. Toxicol In Vitro 29:259–270. doi:10.1016/j.tiv.2014.10.018

    CAS  Article  PubMed  Google Scholar 

  48. Richard AM et al (2016) ToxCast chemical landscape: paving the road to 21st century Toxicology. Chem Res Toxicol 29:1225–1251. doi:10.1021/acs.chemrestox.6b00135

    CAS  Article  PubMed  Google Scholar 

  49. Ritz C, Streibig JC (2005) Bioassay analysis using R. J Stat Softw 12:1–22

    Article  Google Scholar 

  50. Robinson JF, Piersma AH (2013) Toxicogenomic approaches in developmental toxicology testing. Methods Mol Biol 947:451–473. doi:10.1007/978-1-62703-131-8_31

    CAS  Article  PubMed  Google Scholar 

  51. Ryan KR, Sirenko O, Parham F, Hsieh JH, Cromwell EF, Tice RR, Behl M (2016) Neurite outgrowth in human induced pluripotent stem cell-derived neurons as a high-throughput screen for developmental neurotoxicity or neurotoxicity. Neurotoxicology 53:271–281. doi:10.1016/j.neuro.2016.02.003

    CAS  Article  PubMed  Google Scholar 

  52. Sadowski J, Gasteiger J, Klebe G (1994) Comparison of automatic three-dimensional model builders using 639 X-ray structures. J Chem Inf Comput Sci 34:1000–1008. doi:10.1021/ci00020a039

    CAS  Article  Google Scholar 

  53. Schenk B et al (2010) The ReProTect Feasibility Study, a novel comprehensive in vitro approach to detect reproductive toxicants. Reprod Toxicol 30:200–218. doi:10.1016/j.reprotox.2010.05.012

    CAS  Article  PubMed  Google Scholar 

  54. Schmidt BZ et al (2016) In vitro acute and developmental neurotoxicity screening: an overview of cellular platforms and high-throughput technical possibilities. Arch Toxicol. doi:10.1007/s00204-016-1805-9

    Google Scholar 

  55. Schultz L et al (2015) Evaluation of drug-induced neurotoxicity based on metabolomics, proteomics and electrical activity measurements in complementary CNS in vitro models. Toxicol In Vitro 30:138–165. doi:10.1016/j.tiv.2015.05.016

    CAS  Article  PubMed  Google Scholar 

  56. Shinde V et al (2016) Definition of transcriptome-based indices for quantitative characterization of chemically disturbed stem cell development: introduction of the STOP-Toxukn and STOP-Toxukk tests. Arch Toxicol. doi:10.1007/s00204-016-1741-8

    PubMed  PubMed Central  Google Scholar 

  57. Shukla SJ, Huang R, Austin CP, Xia M (2010) The future of toxicity testing: a focus on in vitro methods using a quantitative high-throughput screening platform. Drug Discov Today 15:997–1007. doi:10.1016/j.drudis.2010.07.007

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  58. Smirnova L, Hogberg HT, Leist M, Hartung T (2014) Developmental neurotoxicity—challenges in the 21st century and in vitro opportunities. Altex 31:129–156. doi:10.14573/altex.1403271

    PubMed  PubMed Central  Google Scholar 

  59. Sonneveld E, Jansen HJ, Riteco JA, Brouwer A, van der Burg B (2005) Development of androgen- and estrogen-responsive bioassays, members of a panel of human cell line-based highly selective steroid-responsive bioassays. Toxicol Sci 83:136–148. doi:10.1093/toxsci/kfi005

    CAS  Article  PubMed  Google Scholar 

  60. Stiegler NV, Krug AK, Matt F, Leist M (2011) Assessment of chemical-induced impairment of human neurite outgrowth by multiparametric live cell imaging in high-density cultures. Toxicol Sci 121:73–87. doi:10.1093/toxsci/kfr034

    CAS  Article  PubMed  Google Scholar 

  61. Strickland J et al (2016a) Integrated decision strategies for skin sensitization hazard. J Appl Toxicol 36:1150–1162. doi:10.1002/jat.3281

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  62. Strickland J et al (2016b) Multivariate models for prediction of human skin sensitization hazard. J Appl Toxicol. doi:10.1002/jat.3366

    PubMed Central  Google Scholar 

  63. Tice RR, Austin CP, Kavlock RJ, Bucher JR (2013) Improving the human hazard characterization of chemicals: a Tox21 update. Environ Health Perspect 121:756–765. doi:10.1289/ehp.1205784

    Article  PubMed  PubMed Central  Google Scholar 

  64. USEPA (2016) ToxCast & Tox21 Chemicals from DSSTox_20151019. Retrieved from on 29th July, 2016. Data released 19th Oct 2015

  65. van der Burg B et al (2015) The ChemScreen project to design a pragmatic alternative approach to predict reproductive toxicity of chemicals. Reprod Toxicol 55:114–123. doi:10.1016/j.reprotox.2015.01.008

    Article  PubMed  Google Scholar 

  66. van der Laan JW, Chapin RE, Haenen B, Jacobs AC, Piersma A (2012) Testing strategies for embryo-fetal toxicity of human pharmaceuticals. Animal models vs. in vitro approaches: a workshop report. Regul Toxicol Pharmacol 63:115–123. doi:10.1016/j.yrtph.2012.03.009

    Article  PubMed  Google Scholar 

  67. van Thriel C, Westerink RH, Beste C, Bale AS, Lein PJ, Leist M (2012) Translating neurobehavioural endpoints of developmental neurotoxicity tests into in vitro assays and readouts. Neurotoxicology 33:911–924. doi:10.1016/j.neuro.2011.10.002

    Article  PubMed  Google Scholar 

  68. Zimmer B, Lee G, Balmer NV, Meganathan K, Sachinidis A, Studer L, Leist M (2012) Evaluation of developmental toxicants and signaling pathways in a functional test based on the migration of human neural crest cells. Environ Health Perspect 120:1116–1122. doi:10.1289/ehp.1104489

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  69. Zimmer B et al (2014) Profiling of drugs and environmental chemicals for functional impairment of neural crest migration in a novel stem cell-based test battery. Arch Toxicol 88:1109–1126. doi:10.1007/s00204-014-1231-9

    CAS  PubMed  PubMed Central  Google Scholar 

Download references


This work was supported by the Land BW, the Doerenkamp-Zbinden Foundation, the DFG (RTG1331, KoRS-CB) and the European Project EU-ToxRisk. We are grateful to M. Kapitza, H. Leisner and the staff of the bioimaging center (BIC) and the flow cytometry center (FlowKon) for invaluable experimental support.

Author information



Corresponding author

Correspondence to Marcel Leist.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (XLS 852 kb)

Supplementary material 2 (PDF 1135 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Nyffeler, J., Dolde, X., Krebs, A. et al. Combination of multiple neural crest migration assays to identify environmental toxicants from a proof-of-concept chemical library. Arch Toxicol 91, 3613–3632 (2017).

Download citation


  • Cell migration
  • Cell tracking
  • Cytotoxicity
  • High content imaging
  • Developmental toxicity
  • Human stem cells