High-throughput fluorescence imaging approaches for drug discovery using in vitro and in vivo three-dimensional models

Bibliography

• Abbott A. Cell culture: biology’s new dimension. Nature 2003;424:870-2
   PubMed Web of Science ®Google Scholar
• Weigelt B, Ghajar CM, Bissell MJ. The need for complex 3d culture models to unravel novel pathways and identify accurate biomarkers in breast cancer. Adv Drug Deliv Rev 2014;69-70:42-51
   PubMed Web of Science ®Google Scholar
• Pampaloni F, Reynaud EG, Stelzer EH. The third dimension bridges the gap between cell culture and live tissue. Nat Rev Mol Cell Biol 2007;8:839-45
   PubMed Web of Science ®Google Scholar
• Mazzoleni G, Di Lorenzo D, Steimberg N. Modelling tissues in 3D: The next future of pharmaco-toxicology and food research? Genes Nutr 2009;4:13-22
   PubMed Web of Science ®Google Scholar
• LaBarbera DV, Reid BG, Yoo BH. The multicellular tumor spheroid model for high-throughput cancer drug discovery. Expert opinion on drug discovery 2012;7:819-30
   PubMed Web of Science ®Google Scholar
• Kunz-Schughart LA, Freyer JP, Hofstaedter F, et al. The use of 3-D cultures for high-throughput screening: The multicellular spheroid model. J Biomol Screen 2004;9:273-85
   PubMed Web of Science ®Google Scholar
• Giacomotto J, Segalat L. High-throughput screening and small animal models, where are we? Br J Pharmacol 2010;160:204-16
   PubMed Web of Science ®Google Scholar
• Zon LI, Peterson RT. In vivo drug discovery in the zebrafish. Nat Rev Drug Discov 2005;4:35-44
   PubMed Web of Science ®Google Scholar
• O’Reilly LP, Luke CJ, Perlmutter DH, et al. C. Elegans in high-throughput drug discovery. Adv Drug Deliv Rev 2014;69-70:247-53
   PubMed Web of Science ®Google Scholar
• Breslin S, O’Driscoll L. Three-dimensional cell culture: the missing link in drug discovery. Drug Discov Today 2013;18:240-9
   PubMed Web of Science ®Google Scholar
• Swinney DC, Anthony J. How were new medicines discovered? Nat Rev Drug Discov 2011;10:507-19
   PubMed Web of Science ®Google Scholar
• Astashkina A, Grainger DW. Critical analysis of 3-d organoid in vitro cell culture models for high-throughput drug candidate toxicity assessments. Adv Drug Deliv Rev 2014;69-70:1-18
   PubMed Web of Science ®Google Scholar
• Rizvi I, Celli JP, Evans CL, et al. Synergistic enhancement of carboplatin efficacy with photodynamic therapy in a three-dimensional model for micrometastatic ovarian cancer. Cancer Res 2010;70:9319-28
   PubMed Web of Science ®Google Scholar
• Montanez-Sauri SI, Beebe DJ, Sung KE. Microscale screening systems for 3D cellular microenvironments: Platforms, advances, and challenges. Cell Mol Life Sci 2015;72:237-49
   PubMed Web of Science ®Google Scholar
• Kimlin L, Kassis J, Virador V. 3D in vitro tissue models and their potential for drug screening. Expert Opin Drug Discov 2013;8:1455-66
   PubMed Web of Science ®Google Scholar
• Ranga A, Gjorevski N, Lutolf MP. Drug discovery through stem cell-based organoid models. Adv Drug Deliv Rev 2014;69-70:19-28
   PubMed Web of Science ®Google Scholar
• Nam KH, Smith AS, Lone S, et al. Biomimetic 3D tissue models for advanced high-throughput drug screening. J Lab Autom 2015;20:201-15
   PubMedGoogle Scholar
• Vinci M, Gowan S, Boxall F, et al. Advances in establishment and analysis of three-dimensional tumor spheroid-based functional assays for target validation and drug evaluation. BMC Biol 2012;10:29
   PubMed Web of Science ®Google Scholar
• Soldatow VY, Lecluyse EL, Griffith LG, et al. Models for liver toxicity testing. Toxicol Res (Camb) 2013;2:23-39
   PubMed Web of Science ®Google Scholar
• Rimann M, Laternser S, Gvozdenovic A, et al. An in vitro osteosarcoma 3D microtissue model for drug development. J Biotechnol 2014;189:129-35
   PubMed Web of Science ®Google Scholar
• Yoshii Y, Furukawa T, Waki A, et al. High-throughput screening with nanoimprinting 3D culture for efficient drug development by mimicking the tumor environment. Biomaterials 2015;51:278-89
   PubMed Web of Science ®Google Scholar
• Berg E L, Hsu YC, Lee JA. Consideration of the cellular microenvironment: Physiologically relevant co-culture systems in drug discovery. Adv Drug Deliv Rev 2014;69-70:190-204
   PubMed Web of Science ®Google Scholar
• Hoffmann OI, Ilmberger C, Magosch S, et al. Impact of the spheroid model complexity on drug response. J Biotechnol 2015;205:14-23
   PubMed Web of Science ®Google Scholar
• Kenny HA, Lal-Nag M, White EA, et al. Quantitative high throughput screening using a primary human three-dimensional organotypic culture predicts in vivo efficacy. Nat Commun 2015;6:6220
   PubMed Web of Science ®Google Scholar
• Lee JA, Chu S, Willard FS, et al. Open innovation for phenotypic drug discovery: The pd2 assay panel. J Biomol Screen 2011;16:588-602
   PubMed Web of Science ®Google Scholar
• Ivanov DP, Parker TL, Walker DA, et al. Multiplexing spheroid volume, resazurin and acid phosphatase viability assays for high-throughput screening of tumour spheroids and stem cell neurospheres. PLoS One 2014;9:e103817
   PubMed Web of Science ®Google Scholar
• Friedrich J, Seidel C, Ebner R, et al. Spheroid-based drug screen: considerations and practical approach. Nat Protoc 2009;4:309-24
   PubMed Web of Science ®Google Scholar
• Wenzel C, Riefke B, Grundemann S, et al. 3D high-content screening for the identification of compounds that target cells in dormant tumor spheroid regions. Exp Cell Res 2014;323:131-43
   PubMed Web of Science ®Google Scholar
• Ivascu A, Kubbies M. Rapid generation of single-tumor spheroids for high-throughput cell function and toxicity analysis. J Biomol Screen 2006;11:922-32
   PubMed Web of Science ®Google Scholar
• Hongisto V, Jernstrom S, Fey V, et al. High-throughput 3D screening reveals differences in drug sensitivities between culture models of jimt1 breast cancer cells. PLoS One 2013;8:e77232
   PubMed Web of Science ®Google Scholar
• Tung YC, Hsiao AY, Allen SG, et al. High-throughput 3D spheroid culture and drug testing using a 384 hanging drop array. Analyst 2011;136:473-8
   PubMed Web of Science ®Google Scholar
• Hsiao AY, Tung YC, Qu X, et al. 384 hanging drop arrays give excellent z-factors and allow versatile formation of co-culture spheroids. Biotechnol Bioeng 2012;109:1293-304
   PubMed Web of Science ®Google Scholar
• Cavnar SP, Salomonsson E, Luker KE, et al. Transfer, imaging, and analysis plate for facile handling of 384 hanging drop 3D tissue spheroids. J Lab Autom 2014;19:208-14
   PubMedGoogle Scholar
• Beauchamp P, Moritz W, Kelm JM, et al. Development and characterization of a scaffold-free 3D spheroid model of induced pluripotent stem cell-derived human cardiomyocytes. Tissue Eng Part C Methods 2015;21(8):852-61
   PubMed Web of Science ®Google Scholar
• Timm DM, Chen J, Sing D, et al. A high-throughput three-dimensional cell migration assay for toxicity screening with mobile device-based macroscopic image analysis. Sci Rep 2013;3:3000
   PubMed Web of Science ®Google Scholar
• Guo WM, Loh XJ, Tan EY, et al. Development of a magnetic 3D spheroid platform with potential application for high-throughput drug screening. Mol Pharm 2014;11:2182-9
   PubMed Web of Science ®Google Scholar
• Ong SM, Zhao Z, Arooz T, et al. Engineering a scaffold-free 3D tumor model for in vitro drug penetration studies. Biomaterials 2010;31:1180-90
   PubMed Web of Science ®Google Scholar
• Thoma CR, Stroebel S, Rosch N, et al. A high-throughput-compatible 3D microtissue co-culture system for phenotypic rnai screening applications. J Biomol Screen 2013;18:1330-7
   PubMed Web of Science ®Google Scholar
• Ivanov DP, Parker TL, Walker DA, et al. In vitro co-culture model of medulloblastoma and human neural stem cells for drug delivery assessment. J Biotechnol 2015;205:3-13
   PubMed Web of Science ®Google Scholar
• Howes AL, Richardson RD, Finlay D, et al. 3-dimensional culture systems for anti-cancer compound profiling and high-throughput screening reveal increases in egfr inhibitor-mediated cytotoxicity compared to monolayer culture systems. PLoS One 2014;9:e108283
   PubMed Web of Science ®Google Scholar
• Li Q, Chen C, Kapadia A, et al. 3D models of epithelial-mesenchymal transition in breast cancer metastasis: High-throughput screening assay development, validation, and pilot screen. J Biomol Screen 2011;16:141-54
   PubMed Web of Science ®Google Scholar
• Yoshii Y, Waki A, Yoshida K, et al. The use of nanoimprinted scaffolds as 3D culture models to facilitate spontaneous tumor cell migration and well-regulated spheroid formation. Biomaterials 2011;32:6052-8
   PubMed Web of Science ®Google Scholar
• Cho CH, Park J, Tilles AW, et al. Layered patterning of hepatocytes in co-culture systems using microfabricated stencils. Biotechniques 2010;48:47-52
   PubMed Web of Science ®Google Scholar
• No da Y, Lee SA, Choi YY, et al. Functional 3D human primary hepatocyte spheroids made by co-culturing hepatocytes from partial hepatectomy specimens and human adipose-derived stem cells. PLoS One 2012;7:e50723
   PubMed Web of Science ®Google Scholar
• Krausz E, de Hoogt R, Gustin E, et al. Translation of a tumor microenvironment mimicking 3D tumor growth co-culture assay platform to high-content screening. J Biomol Screen 2013;18:54-66
   PubMed Web of Science ®Google Scholar
• Anderson SN, Towne DL, Burns DJ, et al. A high-throughput soft agar assay for identification of anticancer compound. J Biomol Screen 2007;12:938-45
   PubMed Web of Science ®Google Scholar
• Lovitt CJ, Shelper TB, Avery VM. Miniaturized three-dimensional cancer model for drug evaluation. Assay Drug Dev Technol 2013;11:435-48
   PubMed Web of Science ®Google Scholar
• Horman SR, To J, Orth AP. An hts-compatible 3D colony formation assay to identify tumor-specific chemotherapeutics. J Biomol Screen 2013;18:1298-308
   PubMed Web of Science ®Google Scholar
• Rimann M, Angres B, Patocchi-Tenzer I, et al. Automation of 3D cell culture using chemically defined hydrogels. J Lab Autom 2014;19:191-7
   Google Scholar
• Godugu C, Patel AR, Desai U, et al. Algimatrix based 3D cell culture system as an in-vitro tumor model for anticancer studies. PLoS One 2013;8:e53708
   PubMed Web of Science ®Google Scholar
• Zhang X, Wang W, Yu W, et al. Development of an in vitro multicellular tumor spheroid model using microencapsulation and its application in anticancer drug screening and testing. Biotechnol Prog 2005;21:1289-96
   PubMed Web of Science ®Google Scholar
• Reid BG, Jerjian T, Patel P, et al. Live multicellular tumor spheroid models for high-content imaging and screening in cancer drug discovery. Curr Chem Genom Transl Med 2014;8:27-35
   PubMedGoogle Scholar
• Letamendia A, Quevedo C, Ibarbia I, et al. Development and validation of an automated high-throughput system for zebrafish in vivo screenings. PLoS One 2012;7:e36690
   PubMed Web of Science ®Google Scholar
• Milan DJ. Drugs that induce repolarization abnormalities cause bradycardia in zebrafish. Circulation 2003;107:1355-8
   PubMed Web of Science ®Google Scholar
• Rihel J, Prober DA, Arvanites A, et al. Zebrafish behavioral profiling links drugs to biological targets and rest/wake regulation. Science 2010;327:348-51
   PubMed Web of Science ®Google Scholar
• Pardo-Martin C, Chang TY, Koo BK, et al. High-throughput in vivo vertebrate screening. Nat Methods 2010;7:634-6
   PubMed Web of Science ®Google Scholar
• Vogt A, Cholewinski A, Shen X, et al. Automated image-based phenotypic analysis in zebrafish embryos. Dev Dyn 2009;238:656-63
   PubMed Web of Science ®Google Scholar
• Peravali R, Gehrig J, Giselbrecht S, et al. Automated feature detection and imaging for high-resolution screening of zebrafish embryos. Biotechniques 2011;50:319-24
   PubMed Web of Science ®Google Scholar
• Gehrig J, Reischl M, Kalmar E, et al. Automated high-throughput mapping of promoter-enhancer interactions in zebrafish embryos. Nat Methods 2009;6:911-16
   PubMed Web of Science ®Google Scholar
• Corsi AK, Wightman B, Chalfie M. A transparent window into biology: A primer on caenorhabditis elegans. Genetics 2015;200:387-407
   PubMed Web of Science ®Google Scholar
• Gosai SJ, Kwak JH, Luke CJ, et al. Automated high-content live animal drug screening using c. Elegans expressing the aggregation prone serpin alpha1-antitrypsin z. PLoS One 2010;5:e15460
   PubMed Web of Science ®Google Scholar
• Leung CK, Deonarine A, Strange K, et al. High-throughput screening and biosensing with fluorescent c. elegans strains. J Vis Exp 2011
   Google Scholar
• Leung CK, Wang Y, Malany S, et al. An ultra high-throughput, whole-animal screen for small molecule modulators of a specific genetic pathway in caenorhabditis elegans. PLoS One 2013;8:e62166
   PubMed Web of Science ®Google Scholar
• Moy TI, Conery AL, Larkins-Ford J, et al. High-throughput screen for novel antimicrobials using a whole animal infection model. ACS Chem Biol 2009;4:527-33
   PubMed Web of Science ®Google Scholar
• Giepmans BN, Adams SR, Ellisman MH, et al. The fluorescent toolbox for assessing protein location and function. Science 2006;312:217-24
   PubMed Web of Science ®Google Scholar
• Klein OJ, Bhayana B, Park YJ, et al. In vitro optimization of etnbs-pdt against hypoxic tumor environments with a tiered, high-content, 3D model optical screening platform. Mol Pharm 2012;9:3171-82
   PubMed Web of Science ®Google Scholar
• Vamvakidou AP, Mondrinos MJ, Petushi SP, et al. Heterogeneous breast tumoroids: An in vitro assay for investigating cellular heterogeneity and drug delivery. J Biomol Screen 2007;12:13-20
   PubMed Web of Science ®Google Scholar
• Wittig R, Richter V, Wittig-Blaich S, et al. Biosensor-expressing spheroid cultures for imaging of drug-induced effects in three dimensions. J Biomol Screen 2013;18:736-43
   PubMed Web of Science ®Google Scholar
• Lin S, Zhao Y, Xia T, et al. High content screening in zebrafish speeds up hazard ranking of transition metal oxide nanoparticles. ACS Nano 2011;5:7284-95
   PubMed Web of Science ®Google Scholar
• Gallardo VE, Varshney GK, Lee M, et al. Phenotype-driven chemical screening in zebrafish for compounds that inhibit collective cell migration identifies multiple pathways potentially involved in metastatic invasion. Dis Model Mech 2015;8:565-76
   PubMed Web of Science ®Google Scholar
• Tsuji Y, Takahashi N, Fletcher JG, et al. Subtraction color map of contrast-enhanced and unenhanced ct for the prediction of pancreatic necrosis in early stage of acute pancreatitis. AJR Am J Roentgenol 2014;202:W349-56
   PubMed Web of Science ®Google Scholar
• Tsuji N, Ninov N, Delawary M, et al. Whole organism high content screening identifies stimulators of pancreatic beta-cell proliferation. PLoS One 2014;9:e104112
   PubMed Web of Science ®Google Scholar
• Maglioni S, Arsalan N, Franchi L, et al. An automated phenotype-based microscopy screen to identify pro-longevity interventions acting through mitochondria in c. Elegans. Biochim Biophys Acta 2015. [Epub ahead of print]
   Google Scholar
• Kerr RA. Imaging the activity of neurons and muscles. WormBook 2006;1-13
   PubMedGoogle Scholar
• Available from: https://www.microscopyu.com/articles/formulas/formulasfielddepth.html
   Google Scholar
• Godin AG, Lounis B, Cognet L. Super-resolution microscopy approaches for live cell imaging. Biophys J 2014;107:1777-84
   PubMed Web of Science ®Google Scholar
• Lee MK, Rai P, Williams J, et al. Small-molecule labeling of live cell surfaces for three-dimensional super-resolution microscopy. J Am Chem Soc 2014;136:14003-6
   PubMed Web of Science ®Google Scholar
• Winter PW, Chandris P, Fischer RS, et al. Incoherent structured illumination improves optical sectioning and contrast in multiphoton super-resolution microscopy. Opt Express 2015;23:5327-34
   PubMed Web of Science ®Google Scholar
• Chen BC, Legant WR, Wang K, et al. Lattice light-sheet microscopy: Imaging molecules to embryos at high spatiotemporal resolution. Science 2014;346:1257998
   PubMed Web of Science ®Google Scholar
• Pampaloni F, Ansari N, Stelzer EH. High-resolution deep imaging of live cellular spheroids with light-sheet-based fluorescence microscopy. Cell Tissue Res 2013;352:161-77
   PubMed Web of Science ®Google Scholar
• Konig K, Uchugonova A, Gorjup E. Multiphoton fluorescence lifetime imaging of 3D-stem cell spheroids during differentiation. Microsc Res Tech 2011;74:9-17
   PubMed Web of Science ®Google Scholar
• Swedlow JR. Quantitative fluorescence microscopy and image deconvolution. Methods Cell Biol 2013;114:407-26
   PubMed Web of Science ®Google Scholar
• Schermelleh L, Heintzmann R, Leonhardt H. A guide to super-resolution fluorescence microscopy. J Cell Biol 2010;190:165-75
   PubMed Web of Science ®Google Scholar
• Schindelin J, Arganda-Carreras I, Frise E, et al. Fiji: An open-source platform for biological-image analysis. Nat Methods 2012;9:676-82
   PubMed Web of Science ®Google Scholar
• Carpenter AE, Jones TR, Lamprecht MR, et al. Cellprofiler: Image analysis software for identifying and quantifying cell phenotypes. Genome Biol 2006;7:R100
   PubMed Web of Science ®Google Scholar
• Cornelissen F, Cik M, Gustin E. Phaedra, a protocol-driven system for analysis and validation of high-content imaging and flow cytometry. J Biomol Screen 2012;17:496-506
   PubMed Web of Science ®Google Scholar
• Linkert M, Rueden CT, Allan C, et al. Metadata matters: Access to image data in the real world. J Cell Biol 2010;189:777-82
   PubMed Web of Science ®Google Scholar
• Goldberg IG, Allan C, Burel JM, et al. The open microscopy environment (ome) data model and xml file: Open tools for informatics and quantitative analysis in biological imaging. Genome Biol 2005;6:R47
   PubMed Web of Science ®Google Scholar
• Allan C, Burel JM, Moore J, et al. Omero: Flexible, model-driven data management for experimental biology. Nat Methods 2012;9:245-53
   PubMed Web of Science ®Google Scholar
• Di Z, Klop MJ, Rogkoti VM, et al. Ultra high content image analysis and phenotype profiling of 3D cultured micro-tissues. PLoS One 2014;9:e109688
   PubMed Web of Science ®Google Scholar
• Ollion J, Cochennec J, Loll F, et al. Tango: A generic tool for high-throughput 3D image analysis for studying nuclear organization. Bioinformatics 2013;29:1840-1
   PubMed Web of Science ®Google Scholar
• Bilgin CC, Kim S, Leung E, et al. Integrated profiling of three dimensional cell culture models and 3D microscopy. Bioinformatics 2013;29:3087-93
   PubMed Web of Science ®Google Scholar
• Peng H, Ruan Z, Long F, et al. V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets. Nat Biotechnol 2010;28:348-53
   PubMed Web of Science ®Google Scholar
• Bonnier F, Keating ME, Wrobel TP, et al. Cell viability assessment using the alamar blue assay: A comparison of 2d and 3D cell culture models. Toxicol In Vitro 2015;29:124-31
   PubMed Web of Science ®Google Scholar
• Oshikata A, Matsushita T, Ueoka R. Enhancement of drug efflux activity via mdr1 protein by spheroid culture of human hepatic cancer cells. J Biosci Bioeng 2011;111:590-3
   PubMed Web of Science ®Google Scholar
• Nichols AJ, Roussakis E, Klein OJ, et al. Click-assembled, oxygen-sensing nanoconjugates for depth-resolved, near-infrared imaging in a 3D cancer model. Angew Chem Int Ed Engl 2014;53:3671-4
   PubMed Web of Science ®Google Scholar
• Erturk A, Bradke F. High-resolution imaging of entire organs by 3-dimensional imaging of solvent cleared organs (3disco). Exp Neurol 2013;242:57-64
   PubMed Web of Science ®Google Scholar
• Hama H, Kurokawa H, Kawano H, et al. Scale: A chemical approach for fluorescence imaging and reconstruction of transparent mouse brain. Nat Neurosci 2011;14:1481-8
   PubMed Web of Science ®Google Scholar
• Chung K, Wallace J, Kim SY, et al. Structural and molecular interrogation of intact biological systems. Nature 2013;497:332-7
   PubMed Web of Science ®Google Scholar
• Boutin ME, Hoffman-Kim D. Application and assessment of optical clearing methods for imaging of tissue-engineered neural stem cell spheres. Tissue Eng Part C Methods 2015;21:292-302
   PubMed Web of Science ®Google Scholar
• Wang G, Rajpurohit SK, Delaspre F et al. First quantitative high-throughput screen in zebrafish identifies novel pathways for increasing pancreatic β-cell mass. Elife 2015. 10.7554/eLife.08261
   Google Scholar