Archives of Toxicology

, Volume 91, Issue 11, pp 3613–3632 | Cite as

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

  • Johanna Nyffeler
  • Xenia Dolde
  • Alice Krebs
  • Kevin Pinto-Gil
  • Manuel Pastor
  • Mamta Behl
  • Tanja Waldmann
  • Marcel LeistEmail author
In vitro systems


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.


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



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


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



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.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

204_2017_1977_MOESM1_ESM.xls (852 kb)
Supplementary material 1 (XLS 852 kb)
204_2017_1977_MOESM2_ESM.pdf (1.1 mb)
Supplementary material 2 (PDF 1135 kb)


  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 CrossRefPubMedGoogle 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 PubMedPubMedCentralGoogle Scholar
  3. Bal-Price AK et al (2012) Advancing the science of developmental neurotoxicity (DNT): testing for better safety evaluation. Altex 29:202–215CrossRefPubMedGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 PubMedPubMedCentralGoogle Scholar
  10. Collins FS, Gray GM, Bucher JR (2008) Toxicology. Transforming environmental health protection. Science 319:906–907. doi: 10.1126/science.1154619 CrossRefPubMedPubMedCentralGoogle 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):43–63PubMedGoogle Scholar
  12. Crofton KM et al (2011) Developmental neurotoxicity testing: recommendations for developing alternative methods for the screening and prioritization of chemicals. Altex 28:9–15PubMedGoogle 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 CrossRefGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 PubMedPubMedCentralGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle Scholar
  25. Juberg DR et al (2016) FutureTox III: bridges for translation. Toxicol Sci. doi: 10.1093/toxsci/kfw194 PubMedGoogle Scholar
  26. Judson R et al (2013) Perspectives on validation of high-throughput assays supporting 21st century toxicity testing. Altex 30:51–56CrossRefPubMedPubMedCentralGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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):4530–4539PubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle Scholar
  33. Leist M, Hartung T, Nicotera P (2008) The dawning of a new age of toxicology. Altex 25:103–114CrossRefPubMedGoogle Scholar
  34. Leist M, Efremova L, Karreman C (2010) Food for thought … considerations and guidelines for basic test method descriptions in toxicology. Altex 27:309–317CrossRefPubMedGoogle 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 PubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 PubMedGoogle 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 CrossRefPubMedGoogle 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 43:3233–3243CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 PubMedCentralGoogle 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 CrossRefPubMedGoogle Scholar
  46. R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle Scholar
  49. Ritz C, Streibig JC (2005) Bioassay analysis using R. J Stat Softw 12:1–22CrossRefGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 PubMedPubMedCentralGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 PubMedPubMedCentralGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedPubMedCentralGoogle Scholar
  62. Strickland J et al (2016b) Multivariate models for prediction of human skin sensitization hazard. J Appl Toxicol. doi: 10.1002/jat.3366 PubMedCentralGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 PubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Johanna Nyffeler
    • 1
    • 2
  • Xenia Dolde
    • 1
    • 3
  • Alice Krebs
    • 1
    • 3
  • Kevin Pinto-Gil
    • 4
  • Manuel Pastor
    • 4
  • Mamta Behl
    • 5
  • Tanja Waldmann
    • 1
  • Marcel Leist
    • 1
    • 2
    • 3
    Email author
  1. 1.In Vitro Toxicology and Biomedicine, Department inaugurated by the Doerenkamp-Zbinden FoundationUniversity of KonstanzKonstanzGermany
  2. 2.Research Training Group RTG1331KonstanzGermany
  3. 3.Konstanz Research School Chemical Biology (KoRS-CB)KonstanzGermany
  4. 4.Research Programme on Biomedical Informatics (GRIB), Department of Experimental and Health SciencesUniversitat Pompeu FabraBarcelonaSpain
  5. 5.Division of National Toxicology ProgramNational Institute of Environmental Health SciencesResearch Triangle ParkUSA

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