Advertisement

The Power of Zebrafish in Personalised Medicine

  • Sarah BaxendaleEmail author
  • Freek van Eeden
  • Robert Wilkinson
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1007)

Abstract

The goal of personalised medicine is to develop tailor-made therapies for patients in whom currently available therapeutics fail. This approach requires correlating individual patient genotype data to specific disease phenotype data and using these stratified data sets to identify bespoke therapeutics. Applications for personalised medicine include common complex diseases which may have multiple targets, as well as rare monogenic disorders, for which the target may be unknown. In both cases, whole genome sequence analysis (WGS) is discovering large numbers of disease associated mutations in new candidate genes and potential modifier genes. Currently, the main limiting factor is the determination of which mutated genes are important for disease progression and therefore represent potential targets for drug discovery. Zebrafish have gained popularity as a model organism for understanding developmental processes, disease mechanisms and more recently for drug discovery and toxicity testing. In this chapter, we will examine the diverse roles that zebrafish can make in the expanding field of personalised medicine, from generating humanised disease models to xenograft screening of different cancer cell lines, through to finding new drugs via in vivo phenotypic screens. We will discuss the tools available for zebrafish research and recent advances in techniques, highlighting the advantages and potential of using zebrafish for high throughput disease modeling and precision drug discovery.

Keywords

Zebrafish Personalised medicine CRISPR Xenograft Chemical screen Cancer Neurological disorder Transgenic 

Notes

Acknowledgements

We thank Vincent Cunliffe for comments on the manuscript. SB is funded by a grant from the BBSRC (BB/M01021X/1) and FvE was funded by BBSRC (BB/M02332X/1). The Sheffield zebrafish aquarium and small molecule screening facilities are supported by grants from the MRC (G0700091, G0802527).

References

  1. 1.
    Davis EE, Frangakis S, Katsanis N (2014) Interpreting human genetic variation with in vivo zebrafish assays. Biochim Biophys Acta 1842:1960–1970. doi: 10.1016/j.bbadis.2014.05.024 PubMedPubMedCentralCrossRefGoogle Scholar
  2. 2.
    Howe K et al (2013) The zebrafish reference genome sequence and its relationship to the human genome. Nature 496:498–503. doi: 10.1038/nature12111 PubMedPubMedCentralCrossRefGoogle Scholar
  3. 3.
    Cox DB, Platt RJ, Zhang F (2015) Therapeutic genome editing: prospects and challenges. Nat Med 21:121–131. doi: 10.1038/nm.3793 PubMedPubMedCentralCrossRefGoogle Scholar
  4. 4.
    Reardon S (2015) Leukaemia success heralds wave of gene-editing therapies. Nature 527:146–147. doi: 10.1038/nature.2015.18737 PubMedCrossRefGoogle Scholar
  5. 5.
    Doyon Y et al (2008) Heritable targeted gene disruption in zebrafish using designed zinc-finger nucleases. Nat Biotechnol 26:702–708. doi: 10.1038/nbt1409 PubMedPubMedCentralCrossRefGoogle Scholar
  6. 6.
    Meng X, Noyes MB, Zhu LJ, Lawson ND, Wolfe SA (2008) Targeted gene inactivation in zebrafish using engineered zinc-finger nucleases. Nat Biotechnol 26:695–701. doi: 10.1038/nbt1398 PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Sander JD et al (2011) Selection-free zinc-finger-nuclease engineering by context-dependent assembly (CoDA). Nat Methods 8:67–69. doi: 10.1038/nmeth.1542 PubMedCrossRefGoogle Scholar
  8. 8.
    Cade L et al (2012) Highly efficient generation of heritable zebrafish gene mutations using homo- and heterodimeric TALENs. Nucleic Acids Res 40:8001–8010. doi: 10.1093/nar/gks518 PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Sander JD et al (2011) Targeted gene disruption in somatic zebrafish cells using engineered TALENs. Nat Biotechnol 29:697–698. doi: 10.1038/nbt.1934 PubMedPubMedCentralCrossRefGoogle Scholar
  10. 10.
    Hwang WY et al (2013) Efficient genome editing in zebrafish using a CRISPR-Cas system. Nat Biotechnol 31:227–229. doi: 10.1038/nbt.2501 PubMedPubMedCentralCrossRefGoogle Scholar
  11. 11.
    Hruscha A et al (2013) Efficient CRISPR/Cas9 genome editing with low off-target effects in zebrafish. Development 140:4982–4987. doi: 10.1242/dev.099085 PubMedCrossRefGoogle Scholar
  12. 12.
    Sertori R, Trengove M, Basheer F, Ward AC, Liongue C (2016) Genome editing in zebrafish: a practical overview. Brief Funct Genomics 15:322–330. doi: 10.1093/bfgp/elv051 PubMedCrossRefGoogle Scholar
  13. 13.
    Ear J et al (2016) A zebrafish model of 5q-syndrome using CRISPR/Cas9 targeting RPS14 reveals a p53-independent and p53-dependent mechanism of erythroid failure. J Genet Genomics 43:307–318. doi: 10.1016/j.jgg.2016.03.007 PubMedCrossRefGoogle Scholar
  14. 14.
    Zhang Y et al (2014) Defects of protein production in erythroid cells revealed in a zebrafish Diamond-Blackfan anemia model for mutation in RPS19. Cell Death Dis 5:e1352. doi: 10.1038/cddis.2014.318 PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Wilkinson RN, Jopling C, van Eeden FJ (2014) Zebrafish as a model of cardiac disease. Prog Mol Biol Transl Sci 124:65–91. doi: 10.1016/B978-0-12-386930-2.00004-5 PubMedCrossRefGoogle Scholar
  16. 16.
    Wilkinson RN, van Eeden FJ (2014) The zebrafish as a model of vascular development and disease. Prog Mol Biol Transl Sci 124:93–122. doi: 10.1016/B978-0-12-386930-2.00005-7 PubMedCrossRefGoogle Scholar
  17. 17.
    Schmid B, Haass C (2013) Genomic editing opens new avenues for zebrafish as a model for neurodegeneration. J Neurochem 127:461–470. doi: 10.1111/jnc.12460 PubMedCrossRefGoogle Scholar
  18. 18.
    Martin-Jimenez R, Campanella M, Russell C (2015) New zebrafish models of neurodegeneration. Curr Neurol Neurosci Rep 15:33. doi: 10.1007/s11910-015-0555-z PubMedCrossRefGoogle Scholar
  19. 19.
    Auer TO, Duroure K, Concordet JP, Del Bene F (2014) CRISPR/Cas9-mediated conversion of eGFP- into Gal4-transgenic lines in zebrafish. Nat Protoc 9:2823–2840. doi: 10.1038/nprot.2014.187 PubMedCrossRefGoogle Scholar
  20. 20.
    Auer TO, Duroure K, De Cian A, Concordet JP, Del Bene F (2014) Highly efficient CRISPR/Cas9-mediated knock-in in zebrafish by homology-independent DNA repair. Genome Res 24:142–153. doi: 10.1101/gr.161638.113 PubMedPubMedCentralCrossRefGoogle Scholar
  21. 21.
    Shin J, Chen J, Solnica-Krezel L (2014) Efficient homologous recombination-mediated genome engineering in zebrafish using TALE nucleases. Development 141:3807–3818. doi: 10.1242/dev.108019 PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Zu Y et al (2013) TALEN-mediated precise genome modification by homologous recombination in zebrafish. Nat Methods 10:329–331. doi: 10.1038/nmeth.2374 PubMedCrossRefGoogle Scholar
  23. 23.
    Armstrong GA et al (2016) Homology directed knockin of point mutations in the zebrafish tardbp and fus genes in ALS using the CRISPR/Cas9 system. PLoS One 11:–e0150188. doi: 10.1371/journal.pone.0150188
  24. 24.
    Bedell VM et al (2012) In vivo genome editing using a high-efficiency TALEN system. Nature 491:114–118. doi: 10.1038/nature11537 PubMedPubMedCentralCrossRefGoogle Scholar
  25. 25.
    Gagnon JA et al (2014) Efficient mutagenesis by Cas9 protein-mediated oligonucleotide insertion and large-scale assessment of single-guide RNAs. PLoS One 9:e98186. doi: 10.1371/journal.pone.0098186 PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    Hoshijima K, Jurynec MJ, Grunwald DJ (2016) Precise Editing of the Zebrafish Genome Made Simple and Efficient. Dev Cell 36:654–667. doi: 10.1016/j.devcel.2016.02.015 PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Komor AC, Kim YB, Packer MS, Zuris JA, Liu DR (2016) Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533:420–424. doi: 10.1038/nature17946 PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Amsterdam A et al (2004) Identification of 315 genes essential for early zebrafish development. Proc Natl Acad Sci U S A 101:12792–12797. doi: 10.1073/pnas.0403929101 PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Driever W et al (1996) A genetic screen for mutations affecting embryogenesis in zebrafish. Development 123:37–46PubMedGoogle Scholar
  30. 30.
    Haffter P et al (1996) The identification of genes with unique and essential functions in the development of the zebrafish, Danio rerio. Development 123:1–36PubMedGoogle Scholar
  31. 31.
    Kettleborough RN et al (2013) A systematic genome-wide analysis of zebrafish protein-coding gene function. Nature 496:494–497. doi: 10.1038/nature11992 PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Shah AN, Davey CF, Whitebirch AC, Miller AC, Moens CB (2015) Rapid reverse genetic screening using CRISPR in zebrafish. Nat Methods 12:535–540. doi: 10.1038/nmeth.3360 PubMedPubMedCentralCrossRefGoogle Scholar
  33. 33.
    Kim IS et al (2017) Microenvironment-derived factors driving metastatic plasticity in melanoma. Nat Commun 8:14343. doi: 10.1038/ncomms14343 PubMedPubMedCentralCrossRefGoogle Scholar
  34. 34.
    Sanjana NE (2016) Genome-scale CRISPR pooled screens. Anal Biochem. doi: 10.1016/j.ab.2016.05.014
  35. 35.
    Tsai SQ, Joung JK (2016) Defining and improving the genome-wide specificities of CRISPR-Cas9 nucleases. Nat Rev Genet 17:300–312. doi: 10.1038/nrg.2016.28 PubMedCrossRefGoogle Scholar
  36. 36.
    Kleinstiver BP et al (2016) High-fidelity CRISPR-Cas9 nucleases with no detectable genome-wide off-target effects. Nature 529:490–495. doi: 10.1038/nature16526 PubMedPubMedCentralCrossRefGoogle Scholar
  37. 37.
    Feng Y et al (2016) Expanding CRISPR/Cas9 genome editing capacity in zebrafish using SaCas9. G3 (Bethesda) 6:2517–2521. doi: 10.1534/g3.116.031914 CrossRefGoogle Scholar
  38. 38.
    Kleinstiver BP et al (2016) Genome-wide specificities of CRISPR-Cas Cpf1 nucleases in human cells. Nat Biotechnol 34:869–874. doi: 10.1038/nbt.3620 PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Kok FO et al (2015) Reverse genetic screening reveals poor correlation between morpholino-induced and mutant phenotypes in zebrafish. Dev Cell 32:97–108. doi: 10.1016/j.devcel.2014.11.018 PubMedCrossRefGoogle Scholar
  40. 40.
    Novodvorsky P et al (2015) klf2ash317 mutant zebrafish do not recapitulate morpholino-induced vascular and haematopoietic phenotypes. PLoS One 10:e0141611. doi: 10.1371/journal.pone.0141611 PubMedPubMedCentralCrossRefGoogle Scholar
  41. 41.
    Shmukler BE et al (2015) Homozygous knockout of the piezo1 gene in the zebrafish is not associated with anemia. Haematologica 100:e483–e485. doi: 10.3324/haematol.2015.132449 PubMedPubMedCentralCrossRefGoogle Scholar
  42. 42.
    Rossi A et al (2015) Genetic compensation induced by deleterious mutations but not gene knockdowns. Nature 524:230–233. doi: 10.1038/nature14580 PubMedCrossRefGoogle Scholar
  43. 43.
    Diss G et al (2017) Gene duplication can impart fragility, not robustness, in the yeast protein interaction network. Science 355:630–634. doi: 10.1126/science.aai7685 PubMedCrossRefGoogle Scholar
  44. 44.
    Runtuwene V et al (2011) Noonan syndrome gain-of-function mutations in NRAS cause zebrafish gastrulation defects. Dis Model Mech 4:393–399. doi: 10.1242/dmm.007112 PubMedPubMedCentralCrossRefGoogle Scholar
  45. 45.
    Sousa SB et al (2014) Gain-of-function mutations in the phosphatidylserine synthase 1 (PTDSS1) gene cause Lenz-Majewski syndrome. Nat Genet 46:70–76. doi: 10.1038/ng.2829 PubMedCrossRefGoogle Scholar
  46. 46.
    Thermes V et al (2002) I-SceI meganuclease mediates highly efficient transgenesis in fish. Mech Dev 118:91–98PubMedCrossRefGoogle Scholar
  47. 47.
    Kawakami K et al (2004) A transposon-mediated gene trap approach identifies developmentally regulated genes in zebrafish. Dev Cell 7:133–144. doi: 10.1016/j.devcel.2004.06.005 PubMedCrossRefGoogle Scholar
  48. 48.
    Mosimann C et al (2013) Site-directed zebrafish transgenesis into single landing sites with the phiC31 integrase system. Dev Dyn 242:949–963. doi: 10.1002/dvdy.23989 PubMedPubMedCentralCrossRefGoogle Scholar
  49. 49.
    Roberts JA et al (2014) Targeted transgene integration overcomes variability of position effects in zebrafish. Development 141:715–724. doi: 10.1242/dev.100347 PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Langenau DM et al (2003) Myc-induced T cell leukemia in transgenic zebrafish. Science 299:887–890. doi: 10.1126/science.1080280 PubMedCrossRefGoogle Scholar
  51. 51.
    Feng H et al (2007) Heat-shock induction of T-cell lymphoma/leukaemia in conditional Cre/lox-regulated transgenic zebrafish. Br J Haematol 138:169–175. doi: 10.1111/j.1365-2141.2007.06625.x PubMedCrossRefGoogle Scholar
  52. 52.
    Chen J et al (2007) NOTCH1-induced T-cell leukemia in transgenic zebrafish. Leukemia 21:462–471. doi: 10.1038/sj.leu.2404546 PubMedCrossRefGoogle Scholar
  53. 53.
    Feng H et al (2010) T-lymphoblastic lymphoma cells express high levels of BCL2, S1P1, and ICAM1, leading to a blockade of tumor cell intravasation. Cancer Cell 18:353–366. doi: 10.1016/j.ccr.2010.09.009 PubMedPubMedCentralCrossRefGoogle Scholar
  54. 54.
    Patton EE et al (2005) BRAF mutations are sufficient to promote nevi formation and cooperate with p53 in the genesis of melanoma. Curr Biol 15:249–254. doi: 10.1016/j.cub.2005.01.031 PubMedCrossRefGoogle Scholar
  55. 55.
    Davies H et al (2002) Mutations of the BRAF gene in human cancer. Nature 417:949–954. doi: 10.1038/nature00766 PubMedCrossRefGoogle Scholar
  56. 56.
    O'Donnell KC et al (2014) Axon degeneration and PGC-1alpha-mediated protection in a zebrafish model of alpha-synuclein toxicity. Dis Model Mech 7:571–582. doi: 10.1242/dmm.013185 PubMedPubMedCentralCrossRefGoogle Scholar
  57. 57.
    Ohki Y et al (2017) Glycine-alanine dipeptide repeat protein contributes to toxicity in a zebrafish model of C9orf72 associated neurodegeneration. Mol Neurodegener 12:6. doi: 10.1186/s13024-016-0146-8 PubMedPubMedCentralCrossRefGoogle Scholar
  58. 58.
    Jindal GA et al (2017) In vivo severity ranking of Ras pathway mutations associated with developmental disorders. Proc Natl Acad Sci U S A 114:510–515. doi: 10.1073/pnas.1615651114 PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Tsetskhladze ZR et al (2012) Functional assessment of human coding mutations affecting skin pigmentation using zebrafish. PLoS One 7:e47398. doi: 10.1371/journal.pone.0047398 PubMedPubMedCentralCrossRefGoogle Scholar
  60. 60.
    Waters MF et al (2006) Mutations in voltage-gated potassium channel KCNC3 cause degenerative and developmental central nervous system phenotypes. Nat Genet 38:447–451. doi: 10.1038/ng1758 PubMedCrossRefGoogle Scholar
  61. 61.
    Issa FA, Mazzochi C, Mock AF, Papazian DM (2011) Spinocerebellar ataxia type 13 mutant potassium channel alters neuronal excitability and causes locomotor deficits in zebrafish. J Neurosci 31:6831–6841. doi: 10.1523/JNEUROSCI.6572-10.2011 PubMedPubMedCentralCrossRefGoogle Scholar
  62. 62.
    Gonzaga-Jauregui C et al (2015) Exome sequence analysis suggests that genetic burden contributes to phenotypic variability and complex neuropathy. Cell Rep 12:1169–1183. doi: 10.1016/j.celrep.2015.07.023 PubMedPubMedCentralCrossRefGoogle Scholar
  63. 63.
    Bedell VM, Westcot SE, Ekker SC (2011) Lessons from morpholino-based screening in zebrafish. Brief Funct Genomics 10:181–188. doi: 10.1093/bfgp/elr021 PubMedPubMedCentralCrossRefGoogle Scholar
  64. 64.
    Sia D, Moeini A, Labgaa I, Villanueva A (2015) The future of patient-derived tumor xenografts in cancer treatment. Pharmacogenomics 16:1671–1683. doi: 10.2217/pgs.15.102 PubMedCrossRefGoogle Scholar
  65. 65.
    Malaney P, Nicosia SV, Dave V (2014) One mouse, one patient paradigm: new avatars of personalized cancer therapy. Cancer Lett 344:1–12. doi: 10.1016/j.canlet.2013.10.010 PubMedCrossRefGoogle Scholar
  66. 66.
    Garralda E et al (2014) Integrated next-generation sequencing and avatar mouse models for personalized cancer treatment. Clin Cancer Res 20:2476–2484. doi: 10.1158/1078-0432.CCR-13-3047 PubMedPubMedCentralCrossRefGoogle Scholar
  67. 67.
    Lam SH, Chua HL, Gong Z, Lam TJ, Sin YM (2004) Development and maturation of the immune system in zebrafish, Danio rerio: a gene expression profiling, in situ hybridization and immunological study. Dev Comp Immunol 28:9–28PubMedCrossRefGoogle Scholar
  68. 68.
    Pelster B, Burggren WW (1996) Disruption of hemoglobin oxygen transport does not impact oxygen-dependent physiological processes in developing embryos of zebra fish (Danio rerio). Circ Res 79:358–362PubMedCrossRefGoogle Scholar
  69. 69.
    Rouhi P et al (2010) Hypoxia-induced metastasis model in embryonic zebrafish. Nat Protoc 5:1911–1918. doi: 10.1038/nprot.2010.150 PubMedCrossRefGoogle Scholar
  70. 70.
    Schnurr ME, Yin Y, Scott GR (2014) Temperature during embryonic development has persistent effects on metabolic enzymes in the muscle of zebrafish. J Exp Biol 217:1370–1380. doi: 10.1242/jeb.094037 PubMedCrossRefGoogle Scholar
  71. 71.
    Haldi M, Ton C, Seng WL, McGrath P (2006) Human melanoma cells transplanted into zebrafish proliferate, migrate, produce melanin, form masses and stimulate angiogenesis in zebrafish. Angiogenesis 9:139–151. doi: 10.1007/s10456-006-9040-2 PubMedCrossRefGoogle Scholar
  72. 72.
    Spence R, Gerlach G, Lawrence C, Smith C (2008) The behaviour and ecology of the zebrafish, Danio rerio. Biol Rev Camb Philos Soc 83:13–34. doi: 10.1111/j.1469-185X.2007.00030.x PubMedCrossRefGoogle Scholar
  73. 73.
    Tulotta C et al (2016) Imaging of human cancer cell proliferation, invasion, and micrometastasis in a zebrafish xenogeneic engraftment model. Methods Mol Biol 1451:155–169. doi: 10.1007/978-1-4939-3771-4_11 PubMedCrossRefGoogle Scholar
  74. 74.
    Drabsch Y, He S, Zhang L, Snaar-Jagalska BE, ten Dijke P (2013) Transforming growth factor-beta signalling controls human breast cancer metastasis in a zebrafish xenograft model. Breast Cancer Res 15:R106. doi: 10.1186/bcr3573 PubMedPubMedCentralCrossRefGoogle Scholar
  75. 75.
    Pruvot B et al (2011) Leukemic cell xenograft in zebrafish embryo for investigating drug efficacy. Haematologica 96:612–616. doi: 10.3324/haematol.2010.031401 PubMedPubMedCentralCrossRefGoogle Scholar
  76. 76.
    Nicoli S, Ribatti D, Cotelli F, Presta M (2007) Mammalian tumor xenografts induce neovascularization in zebrafish embryos. Cancer Res 67:2927–2931. doi: 10.1158/0008-5472.CAN-06-4268 PubMedCrossRefGoogle Scholar
  77. 77.
    He S et al (2012) Neutrophil-mediated experimental metastasis is enhanced by VEGFR inhibition in a zebrafish xenograft model. J Pathol 227:431–445. doi: 10.1002/path.4013 PubMedPubMedCentralCrossRefGoogle Scholar
  78. 78.
    Jung DW et al (2012) A novel zebrafish human tumor xenograft model validated for anti-cancer drug screening. Mol BioSyst 8:1930–1939. doi: 10.1039/c2mb05501e PubMedCrossRefGoogle Scholar
  79. 79.
    White RM et al (2008) Transparent adult zebrafish as a tool for in vivo transplantation analysis. Cell Stem Cell 2:183–189. doi: 10.1016/j.stem.2007.11.002 PubMedPubMedCentralCrossRefGoogle Scholar
  80. 80.
    Stoletov K, Montel V, Lester RD, Gonias SL, Klemke R (2007) High-resolution imaging of the dynamic tumor cell vascular interface in transparent zebrafish. Proc Natl Acad Sci U S A 104:17406–17411. doi: 10.1073/pnas.0703446104 PubMedPubMedCentralCrossRefGoogle Scholar
  81. 81.
    Tang Q et al (2014) Optimized cell transplantation using adult rag2 mutant zebrafish. Nat Methods 11:821–824. doi: 10.1038/nmeth.3031 PubMedPubMedCentralCrossRefGoogle Scholar
  82. 82.
    Jung IH et al (2016) Impaired lymphocytes development and xenotransplantation of gastrointestinal tumor cells in Prkdc-Null SCID zebrafish model. Neoplasia 18:468–479. doi: 10.1016/j.neo.2016.06.007 PubMedPubMedCentralCrossRefGoogle Scholar
  83. 83.
    Zhang B et al (2016) Novel immunologic tolerance of human cancer cell xenotransplants in zebrafish. Transl Res 170:89–98 e81–83. doi: 10.1016/j.trsl.2015.12.007 PubMedCrossRefGoogle Scholar
  84. 84.
    Bentley VL et al (2015) Focused chemical genomics using zebrafish xenotransplantation as a pre-clinical therapeutic platform for T-cell acute lymphoblastic leukemia. Haematologica 100:70–76. doi: 10.3324/haematol.2014.110742 PubMedPubMedCentralCrossRefGoogle Scholar
  85. 85.
    Rampazzo E et al (2013) Wnt activation promotes neuronal differentiation of glioblastoma. Cell Death Dis 4:e500. doi: 10.1038/cddis.2013.32 PubMedPubMedCentralCrossRefGoogle Scholar
  86. 86.
    Marques IJ et al (2009) Metastatic behaviour of primary human tumours in a zebrafish xenotransplantation model. BMC Cancer 9:128. doi: 10.1186/1471-2407-9-128 PubMedPubMedCentralCrossRefGoogle Scholar
  87. 87.
    Mercatali, L. et al (2016) Development of a patient-derived xenograft (PDX) of breast cancer bone metastasis in a zebrafish model. Int J Mol Sci 17, doi:10.3390/ijms17081375Google Scholar
  88. 88.
    Gaudenzi G et al (2016) Patient-derived xenograft in zebrafish embryos: a new platform for translational research in neuroendocrine tumors. Endocrine. doi: 10.1007/s12020-016-1048-9
  89. 89.
    Lin J et al (2016) A clinically relevant in vivo zebrafish model of human multiple myeloma to study preclinical therapeutic efficacy. Blood 128:249–252. doi: 10.1182/blood-2016-03-704460 PubMedPubMedCentralCrossRefGoogle Scholar
  90. 90.
    Bansal N et al (2014) Enrichment of human prostate cancer cells with tumor initiating properties in mouse and zebrafish xenografts by differential adhesion. Prostate 74:187–200. doi: 10.1002/pros.22740 PubMedCrossRefGoogle Scholar
  91. 91.
    Staal FJ, Spaink HP, Fibbe WE (2016) Visualizing human hematopoietic stem cell trafficking in vivo using a zebrafish xenograft model. Stem Cells Dev 25:360–365. doi: 10.1089/scd.2015.0195 PubMedCrossRefGoogle Scholar
  92. 92.
    Li J et al (2015) Xenotransplantation of human adipose-derived stem cells in zebrafish embryos. PLoS One 10:e0123264. doi: 10.1371/journal.pone.0123264 PubMedPubMedCentralCrossRefGoogle Scholar
  93. 93.
    Patel N et al (2012) Developmental regulation of TAC1 in peptidergic-induced human mesenchymal stem cells: implication for spinal cord injury in zebrafish. Stem Cells Dev 21:308–320. doi: 10.1089/scd.2011.0179 PubMedCrossRefGoogle Scholar
  94. 94.
    Xia H et al (2014) Identification of a cell-of-origin for fibroblasts comprising the fibrotic reticulum in idiopathic pulmonary fibrosis. Am J Pathol 184:1369–1383. doi: 10.1016/j.ajpath.2014.01.012 PubMedPubMedCentralCrossRefGoogle Scholar
  95. 95.
    Lee LM, Seftor EA, Bonde G, Cornell RA, Hendrix MJ (2005) The fate of human malignant melanoma cells transplanted into zebrafish embryos: assessment of migration and cell division in the absence of tumor formation. Dev Dyn 233:1560–1570. doi: 10.1002/dvdy.20471 PubMedCrossRefGoogle Scholar
  96. 96.
    Benyumov AO et al (2012) A novel zebrafish embryo xenotransplantation model to study primary human fibroblast motility in health and disease. Zebrafish 9:38–43. doi: 10.1089/zeb.2011.0705 PubMedPubMedCentralCrossRefGoogle Scholar
  97. 97.
    Chan XY et al (2015) Three- dimensional vascular network assembly from diabetic patient-derived induced pluripotent stem cells. Arterioscler Thromb Vasc Biol 35:2677–2685. doi: 10.1161/ATVBAHA.115.306362 PubMedPubMedCentralCrossRefGoogle Scholar
  98. 98.
    Orlova VV et al (2014) Functionality of endothelial cells and pericytes from human pluripotent stem cells demonstrated in cultured vascular plexus and zebrafish xenografts. Arterioscler Thromb Vasc Biol 34:177–186. doi: 10.1161/ATVBAHA.113.302598 PubMedCrossRefGoogle Scholar
  99. 99.
    Orlova VV et al (2014) Generation, expansion and functional analysis of endothelial cells and pericytes derived from human pluripotent stem cells. Nat Protoc 9:1514–1531. doi: 10.1038/nprot.2014.102 PubMedCrossRefGoogle Scholar
  100. 100.
    MacRae CA, Peterson RT (2015) Zebrafish as tools for drug discovery. Nat Rev Drug Discov 14:721–731. doi: 10.1038/nrd4627 PubMedCrossRefGoogle Scholar
  101. 101.
    Strange K (2016) Drug discovery in fish, flies, and worms. ILAR J 57:133–143. doi: 10.1093/ilar/ilw034 PubMedCrossRefGoogle Scholar
  102. 102.
    Swinney DC (2013) Phenotypic vs. target-based drug discovery for first-in-class medicines. Clin Pharmacol Ther 93:299–301. doi: 10.1038/clpt.2012.236 PubMedCrossRefGoogle Scholar
  103. 103.
    Peterson RT, Link BA, Dowling JE, Schreiber SL (2000) Small molecule developmental screens reveal the logic and timing of vertebrate development. Proc Natl Acad Sci U S A 97:12965–12969. doi: 10.1073/pnas.97.24.12965 PubMedPubMedCentralCrossRefGoogle Scholar
  104. 104.
    Rennekamp AJ, Peterson RT (2015) 15 years of zebrafish chemical screening. Curr Opin Chem Biol 24:58–70. doi: 10.1016/j.cbpa.2014.10.025 PubMedCrossRefGoogle Scholar
  105. 105.
    Baxendale S et al (2012) Identification of compounds with anti-convulsant properties in a zebrafish model of epileptic seizures. Dis Model Mech 5:773–784. doi: 10.1242/dmm.010090 PubMedPubMedCentralCrossRefGoogle Scholar
  106. 106.
    North TE et al (2007) Prostaglandin E2 regulates vertebrate haematopoietic stem cell homeostasis. Nature 447:1007–1011. doi: 10.1038/nature05883 PubMedPubMedCentralCrossRefGoogle Scholar
  107. 107.
    Robertson AL et al (2014) A zebrafish compound screen reveals modulation of neutrophil reverse migration as an anti-inflammatory mechanism. Sci Transl Med 6:225ra229. doi: 10.1126/scitranslmed.3007672 CrossRefGoogle Scholar
  108. 108.
    Gallardo VE et al (2015) Phenotype-driven chemical screening in zebrafish for compounds that inhibit collective cell migration identifies multiple pathways potentially involved in metastatic invasion. Dis Model Mech 8:565–576. doi: 10.1242/dmm.018689 PubMedPubMedCentralCrossRefGoogle Scholar
  109. 109.
    Kokel D et al (2010) Rapid behavior-based identification of neuroactive small molecules in the zebrafish. Nat Chem Biol 6:231–237. doi: 10.1038/nchembio.307 PubMedPubMedCentralCrossRefGoogle Scholar
  110. 110.
    Rihel J et al (2010) Zebrafish behavioral profiling links drugs to biological targets and rest/wake regulation. Science 327:348–351. doi: 10.1126/science.1183090 PubMedPubMedCentralCrossRefGoogle Scholar
  111. 111.
    Asimaki A et al (2014) Identification of a new modulator of the intercalated disc in a zebrafish model of arrhythmogenic cardiomyopathy. Sci Transl Med 6:240ra274. doi: 10.1126/scitranslmed.3008008 CrossRefGoogle Scholar
  112. 112.
    Peal DS et al (2011) Novel chemical suppressors of long QT syndrome identified by an in vivo functional screen. Circulation 123:23–30. doi: 10.1161/CIRCULATIONAHA.110.003731 PubMedCrossRefGoogle Scholar
  113. 113.
    Yeh JR et al (2008) AML1-ETO reprograms hematopoietic cell fate by downregulating scl expression. Development 135:401–410. doi: 10.1242/dev.008904 PubMedCrossRefGoogle Scholar
  114. 114.
    Owens KN et al (2008) Identification of genetic and chemical modulators of zebrafish mechanosensory hair cell death. PLoS Genet 4:e1000020. doi: 10.1371/journal.pgen.1000020 PubMedPubMedCentralCrossRefGoogle Scholar
  115. 115.
    White RM et al (2011) DHODH modulates transcriptional elongation in the neural crest and melanoma. Nature 471:518–522. doi: 10.1038/nature09882 PubMedPubMedCentralCrossRefGoogle Scholar
  116. 116.
    Kaufman CK et al (2016) A zebrafish melanoma model reveals emergence of neural crest identity during melanoma initiation. Science 351:aad2197. doi: 10.1126/science.aad2197 PubMedPubMedCentralCrossRefGoogle Scholar
  117. 117.
    Kalueff AV et al (2013) Towards a comprehensive catalog of zebrafish behavior 1.0 and beyond. Zebrafish 10:70–86. doi: 10.1089/zeb.2012.0861 PubMedPubMedCentralCrossRefGoogle Scholar
  118. 118.
    Kalueff AV et al (2016) Zebrafish neurobehavioral phenomics for aquatic neuropharmacology and toxicology research. Aquat Toxicol 170:297–309. doi: 10.1016/j.aquatox.2015.08.007 PubMedCrossRefGoogle Scholar
  119. 119.
    Stewart AM et al (2015) A novel 3D method of locomotor analysis in adult zebrafish: implications for automated detection of CNS drug-evoked phenotypes. J Neurosci Methods 255:66–74. doi: 10.1016/j.jneumeth.2015.07.023 PubMedCrossRefGoogle Scholar
  120. 120.
    Rennekamp AJ et al (2016) sigma1 receptor ligands control a switch between passive and active threat responses. Nat Chem Biol 12:552–558. doi: 10.1038/nchembio.2089 PubMedPubMedCentralCrossRefGoogle Scholar
  121. 121.
    Bruni G et al (2016) Zebrafish behavioral profiling identifies multitarget antipsychotic-like compounds. Nat Chem Biol 12:559–566. doi: 10.1038/nchembio.2097 PubMedPubMedCentralCrossRefGoogle Scholar
  122. 122.
    Cunliffe VT (2016) Building a zebrafish toolkit for investigating the pathobiology of epilepsy and identifying new treatments for epileptic seizures. J Neurosci Methods 260:91–95. doi: 10.1016/j.jneumeth.2015.07.015 PubMedCrossRefGoogle Scholar
  123. 123.
    Winter MJ et al (2008) Validation of a larval zebrafish locomotor assay for assessing the seizure liability of early-stage development drugs. J Pharmacol Toxicol Methods 57:176–187. doi: 10.1016/j.vascn.2008.01.004 PubMedCrossRefGoogle Scholar
  124. 124.
    Baraban SC, Taylor MR, Castro PA, Baier H (2005) Pentylenetetrazole induced changes in zebrafish behavior, neural activity and c-fos expression. Neuroscience 131:759–768. doi: 10.1016/j.neuroscience.2004.11.031 PubMedCrossRefGoogle Scholar
  125. 125.
    Dravet C, Bureau M, Oguni H, Fukuyama Y, Cokar O (2005) Severe myoclonic epilepsy in infancy: Dravet syndrome. Adv Neurol 95:71–102PubMedGoogle Scholar
  126. 126.
    Baraban SC, Dinday MT, Hortopan GA (2013) Drug screening in Scn1a zebrafish mutant identifies clemizole as a potential Dravet syndrome treatment. Nat Commun 4:2410. doi: 10.1038/ncomms3410 PubMedPubMedCentralCrossRefGoogle Scholar
  127. 127.
    Griffin A et al (2017) Clemizole and modulators of serotonin signalling suppress seizures in Dravet syndrome. Brain. doi: 10.1093/brain/aww342
  128. 128.
    Bracken MB (2009) Why animal studies are often poor predictors of human reactions to exposure. J R Soc Med 102:120–122. doi: 10.1258/jrsm.2008.08k033 PubMedPubMedCentralCrossRefGoogle Scholar
  129. 129.
    Seok J et al (2013) Genomic responses in mouse models poorly mimic human inflammatory diseases. Proc Natl Acad Sci U S A 110:3507–3512. doi: 10.1073/pnas.1222878110 PubMedPubMedCentralCrossRefGoogle Scholar
  130. 130.
    Rice J (2012) Animal models: not close enough. Nature 484:S9PubMedCrossRefGoogle Scholar
  131. 131.
    Eliceiri BP, Gonzalez AM, Baird A (2011) Zebrafish model of the blood-brain barrier: morphological and permeability studies. Methods Mol Biol 686:371–378. doi: 10.1007/978-1-60761-938-3_18 PubMedPubMedCentralCrossRefGoogle Scholar
  132. 132.
    Fleming A, Diekmann H, Goldsmith P (2013) Functional characterisation of the maturation of the blood-brain barrier in larval zebrafish. PLoS One 8:e77548. doi: 10.1371/journal.pone.0077548 PubMedPubMedCentralCrossRefGoogle Scholar
  133. 133.
    Tam SJ et al (2012) Death receptors DR6 and TROY regulate brain vascular development. Dev Cell 22:403–417. doi: 10.1016/j.devcel.2011.11.018 PubMedCrossRefGoogle Scholar
  134. 134.
    Goldstone JV et al (2010) Identification and developmental expression of the full complement of Cytochrome P450 genes in Zebrafish. BMC Genomics 11:643. doi: 10.1186/1471-2164-11-643 PubMedPubMedCentralCrossRefGoogle Scholar
  135. 135.
    Verbueken E et al (2017) In vitro biotransformation of two human CYP3A probe substrates and their inhibition during early zebrafish development. Int J Mol Sci 18. doi: 10.3390/ijms18010217
  136. 136.
    Martignoni M, Groothuis G, de Kanter R (2006) Comparison of mouse and rat cytochrome P450-mediated metabolism in liver and intestine. Drug Metab Dispos 34:1047–1054. doi: 10.1124/dmd.105.009035 PubMedGoogle Scholar
  137. 137.
    Poon KL et al (2016) Humanizing the zebrafish liver shifts drug metabolic profiles and improves pharmacokinetics of CYP3A4 substrates. Arch Toxicol. doi: 10.1007/s00204-016-1789-5
  138. 138.
    Gootenberg DB, Turnbaugh PJ (2011) Companion animals symposium: humanized animal models of the microbiome. J Anim Sci 89:1531–1537. doi: 10.2527/jas.2010-3371 PubMedCrossRefGoogle Scholar
  139. 139.
    Rawls JF, Mahowald MA, Goodman AL, Trent CM, Gordon JI (2007) In vivo imaging and genetic analysis link bacterial motility and symbiosis in the zebrafish gut. Proc Natl Acad Sci U S A 104:7622–7627. doi: 10.1073/pnas.0702386104 PubMedPubMedCentralCrossRefGoogle Scholar
  140. 140.
    Wittbrodt JN, Liebel U, Gehrig J (2014) Generation of orientation tools for automated zebrafish screening assays using desktop 3D printing. BMC Biotechnol 14:36. doi: 10.1186/1472-6750-14-36 PubMedPubMedCentralCrossRefGoogle Scholar
  141. 141.
    Yanik MF, Rohde CB, Pardo-Martin C (2011) Technologies for micromanipulating, imaging, and phenotyping small invertebrates and vertebrates. Annu Rev Biomed Eng 13:185–217. doi: 10.1146/annurev-bioeng-071910-124703 PubMedCrossRefGoogle Scholar
  142. 142.
    Pulak R (2016) Tools for automating the imaging of zebrafish larvae. Methods 96:118–126. doi: 10.1016/j.ymeth.2015.11.021 PubMedCrossRefGoogle Scholar
  143. 143.
    White DT et al (2016) ARQiv-HTS, a versatile whole-organism screening platform enabling in vivo drug discovery at high-throughput rates. Nat Protoc 11:2432–2453. doi: 10.1038/nprot.2016.142 PubMedPubMedCentralCrossRefGoogle Scholar
  144. 144.
    Collins FS, Varmus H (2015) A new initiative on precision medicine. N Engl J Med 372:793–795. doi: 10.1056/NEJMp1500523 PubMedPubMedCentralCrossRefGoogle Scholar
  145. 145.
    Gahl WA et al (2016) The NIH undiagnosed diseases program and network: applications to modern medicine. Mol Genet Metab 117:393–400. doi: 10.1016/j.ymgme.2016.01.007 PubMedPubMedCentralCrossRefGoogle Scholar
  146. 146.
    Wienholds E, Schulte-Merker S, Walderich B, Plasterk RH (2002) Target-selected inactivation of the zebrafish rag1 gene. Science 297:99–102. doi: 10.1126/science.1071762 PubMedCrossRefGoogle Scholar
  147. 147.
    Varshney GK et al (2013) The Zebrafish Insertion Collection (ZInC): a web based, searchable collection of zebrafish mutations generated by DNA insertion. Nucleic Acids Res 41:D861–D864. doi: 10.1093/nar/gks946 PubMedCrossRefGoogle Scholar
  148. 148.
    Nasevicius A, Ekker SC (2000) Effective targeted gene ‘knockdown’ in zebrafish. Nat Genet 26:216–220. doi: 10.1038/79951 PubMedCrossRefGoogle Scholar
  149. 149.
    Schulte-Merker S, Stainier DY (2014) Out with the old, in with the new: reassessing morpholino knockdowns in light of genome editing technology. Development 141:3103–3104. doi: 10.1242/dev.112003 PubMedCrossRefGoogle Scholar
  150. 150.
    Larson MH et al (2013) CRISPR interference (CRISPRi) for sequence-specific control of gene expression. Nat Protoc 8:2180–2196. doi: 10.1038/nprot.2013.132 PubMedPubMedCentralCrossRefGoogle Scholar
  151. 151.
    Liu SJ et al (2017) CRISPRi-based genome-scale identification of functional long noncoding RNA loci in human cells. Science 355. doi: 10.1126/science.aah7111
  152. 152.
    Weber T, Koster R (2013) Genetic tools for multicolor imaging in zebrafish larvae. Methods 62:279–291. doi: 10.1016/j.ymeth.2013.07.028 PubMedCrossRefGoogle Scholar
  153. 153.
    Halpern ME et al (2008) Gal4/UAS transgenic tools and their application to zebrafish. Zebrafish 5:97–110. doi: 10.1089/zeb.2008.0530 PubMedCrossRefGoogle Scholar
  154. 154.
    Mosimann C, Zon LI (2011) Advanced zebrafish transgenesis with Tol2 and application for Cre/lox recombination experiments. Methods Cell Biol 104:173–194. doi: 10.1016/B978-0-12-374814-0.00010-0 PubMedCrossRefGoogle Scholar
  155. 155.
    Pan YA et al (2013) Zebrabow: multispectral cell labeling for cell tracing and lineage analysis in zebrafish. Development 140:2835–2846. doi: 10.1242/dev.094631 PubMedPubMedCentralCrossRefGoogle Scholar
  156. 156.
    Henninger J et al (2017) Clonal fate mapping quantifies the number of haematopoietic stem cells that arise during development. Nat Cell Biol 19:17–27. doi: 10.1038/ncb3444 PubMedCrossRefGoogle Scholar
  157. 157.
    Moro E et al (2013) Generation and application of signaling pathway reporter lines in zebrafish. Mol Gen Genomics 288:231–242. doi: 10.1007/s00438-013-0750-z CrossRefGoogle Scholar
  158. 158.
    Shimozono S, Iimura T, Kitaguchi T, Higashijima S, Miyawaki A (2013) Visualization of an endogenous retinoic acid gradient across embryonic development. Nature 496:363–366. doi: 10.1038/nature12037 PubMedCrossRefGoogle Scholar
  159. 159.
    Thisse B, Thisse C (2014) In situ hybridization on whole-mount zebrafish embryos and young larvae. Methods Mol Biol 1211:53–67. doi: 10.1007/978-1-4939-1459-3_5 PubMedCrossRefGoogle Scholar
  160. 160.
    Choi HM et al (2016) Mapping a multiplexed zoo of mRNA expression. Development 143:3632–3637. doi: 10.1242/dev.140137 PubMedCrossRefGoogle Scholar
  161. 161.
    Dang M, Henderson RE, Garraway LA, Zon LI (2016) Long-term drug administration in the adult zebrafish using oral gavage for cancer preclinical studies. Dis Model Mech 9:811–820. doi: 10.1242/dmm.024166 PubMedPubMedCentralCrossRefGoogle Scholar
  162. 162.
    Olt J, Allen CE, Marcotti W (2016) In vivo physiological recording from the lateral line of juvenile zebrafish. J Physiol 594:5427–5438. doi: 10.1113/JP271794 PubMedPubMedCentralCrossRefGoogle Scholar
  163. 163.
    Keller PJ (2013) In vivo imaging of zebrafish embryogenesis. Methods 62:268–278. doi: 10.1016/j.ymeth.2013.03.015 PubMedPubMedCentralCrossRefGoogle Scholar
  164. 164.
    Burgess HA, Granato M (2007) Sensorimotor gating in larval zebrafish. J Neurosci 27:4984–4994. doi: 10.1523/JNEUROSCI.0615-07.2007 PubMedCrossRefGoogle Scholar
  165. 165.
    Weber M, Huisken J (2015) In vivo imaging of cardiac development and function in zebrafish using light sheet microscopy. Swiss Med Wkly 145:w14227. doi: 10.4414/smw.2015.14227 PubMedGoogle Scholar
  166. 166.
    Muto A, Kawakami K (2011) Imaging functional neural circuits in zebrafish with a new GCaMP and the Gal4FF-UAS system. Commun Integr Biol 4:566–568. doi: 10.4161/cib.4.5.15848 PubMedPubMedCentralCrossRefGoogle Scholar
  167. 167.
    Prajsnar TK, Cunliffe VT, Foster SJ, Renshaw SA (2008) A novel vertebrate model of Staphylococcus aureus infection reveals phagocyte-dependent resistance of zebrafish to non-host specialized pathogens. Cell Microbiol 10:2312–2325. doi: 10.1111/j.1462-5822.2008.01213.x PubMedCrossRefGoogle Scholar
  168. 168.
    Bojarczuk A et al (2016) Cryptococcus neoformans intracellular proliferation and capsule size determines early macrophage control of infection. Sci Report 6:21489. doi: 10.1038/srep21489 CrossRefGoogle Scholar
  169. 169.
    Harvey SA et al (2013) Identification of the zebrafish maternal and paternal transcriptomes. Development 140:2703–2710. doi: 10.1242/dev.095091 PubMedPubMedCentralCrossRefGoogle Scholar
  170. 170.
    Wardle FC, Muller F (2014) Fish genomics: casting the net wide. Brief Funct Genomics 13:79–81. doi: 10.1093/bfgp/elt055 PubMedCrossRefGoogle Scholar

Copyright information

© American Association of Pharmaceutical Scientists 2017

Authors and Affiliations

  • Sarah Baxendale
    • 1
    Email author
  • Freek van Eeden
    • 1
  • Robert Wilkinson
    • 1
    • 2
  1. 1.The Bateson Centre, Department of Biomedical ScienceUniversity of SheffieldSheffieldUK
  2. 2.Department of Infection, Immunity and Cardiovascular Disease, Medical School, Beech Hill RdUniversity of SheffieldSheffieldUK

Personalised recommendations