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Application of Imaging-Based Assays in Microplate Formats for High-Content Screening

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Book cover High Throughput Screening

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1439))

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Abstract

The use of multiparametric microscopy-based screens with automated analysis has enabled the large-scale study of biological phenomena that are currently not measurable by any other method. Collectively referred to as high-content screening (HCS), or high-content analysis (HCA), these methods rely on an expanding array of imaging hardware and software automation. Coupled with an ever-growing amount of diverse chemical matter and functional genomic tools, HCS has helped open the door to a new frontier of understanding cell biology through phenotype-driven screening. With the ability to interrogate biology on a cell-by-cell basis in highly parallel microplate-based platforms, the utility of HCS continues to grow as advancements are made in acquisition speed, model system complexity, data management, and analysis systems. This chapter uses an example of screening for genetic factors regulating mitochondrial quality control to exemplify the practical considerations in developing and executing high-content campaigns.

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References

  1. Lightowlers RN, Taylor RW, Turnbull DM (2015) Mutations causing mitochondrial disease: what is new and what challenges remain? Science 349(6255):1494–1499. doi:10.1126/science.aac7516

    Article  CAS  Google Scholar 

  2. Wallace DC (2013) A mitochondrial bioenergetic etiology of disease. J Clin Invest 123(4):1405–1412. doi:10.1172/JCI61398

    Article  CAS  Google Scholar 

  3. Klein C, Westenberger A (2012) Genetics of Parkinson’s disease. Cold Spring Harb Perspect Med 2(1):a008888. doi:10.1101/cshperspect.a008888

    Article  Google Scholar 

  4. Nuytemans K, Theuns J, Cruts M, Van Broeckhoven C (2010) Genetic etiology of Parkinson disease associated with mutations in the SNCA, PARK2, PINK1, PARK7, and LRRK2 genes: a mutation update. Hum Mutat 31(7):763–780. doi:10.1002/humu.21277

    Article  CAS  Google Scholar 

  5. Pickrell AM, Youle RJ (2015) The roles of PINK1, parkin, and mitochondrial fidelity in Parkinson’s disease. Neuron 85(2):257–273. doi:10.1016/j.neuron.2014.12.007

    Article  CAS  Google Scholar 

  6. Kane LA, Lazarou M, Fogel AI, Li Y, Yamano K, Sarraf SA, Banerjee S, Youle RJ (2014) PINK1 phosphorylates ubiquitin to activate Parkin E3 ubiquitin ligase activity. J Cell Biol 205(2):143–153. doi:10.1083/jcb.201402104

    Article  CAS  Google Scholar 

  7. Kazlauskaite A, Kondapalli C, Gourlay R, Campbell DG, Ritorto MS, Hofmann K, Alessi DR, Knebel A, Trost M, Muqit MM (2014) Parkin is activated by PINK1-dependent phosphorylation of ubiquitin at Ser65. Biochem J 460(1):127–139. doi:10.1042/BJ20140334

    Article  CAS  Google Scholar 

  8. Koyano F, Okatsu K, Kosako H, Tamura Y, Go E, Kimura M, Kimura Y, Tsuchiya H, Yoshihara H, Hirokawa T, Endo T, Fon EA, Trempe JF, Saeki Y, Tanaka K, Matsuda N (2014) Ubiquitin is phosphorylated by PINK1 to activate parkin. Nature 510(7503):162–166. doi:10.1038/nature13392

    CAS  Google Scholar 

  9. Lazarou M, Sliter DA, Kane LA, Sarraf SA, Wang C, Burman JL, Sideris DP, Fogel AI, Youle RJ (2015) The ubiquitin kinase PINK1 recruits autophagy receptors to induce mitophagy. Nature 524(7565):309–314. doi:10.1038/nature14893

    Article  CAS  Google Scholar 

  10. Narendra D, Tanaka A, Suen DF, Youle RJ (2008) Parkin is recruited selectively to impaired mitochondria and promotes their autophagy. J Cell Biol 183(5):795–803. doi:10.1083/jcb.200809125

    Article  CAS  Google Scholar 

  11. Narendra DP, Jin SM, Tanaka A, Suen DF, Gautier CA, Shen J, Cookson MR, Youle RJ (2010) PINK1 is selectively stabilized on impaired mitochondria to activate Parkin. PLoS Biol 8(1):e1000298. doi:10.1371/journal.pbio.1000298

    Article  Google Scholar 

  12. Hasson SA, Kane LA, Yamano K, Huang CH, Sliter DA, Buehler E, Wang C, Heman-Ackah SM, Hessa T, Guha R, Martin SE, Youle RJ (2013) High-content genome-wide RNAi screens identify regulators of parkin upstream of mitophagy. Nature 504(7479):291–295. doi:10.1038/nature12748

    Article  CAS  Google Scholar 

  13. Hartwell KA, Miller PG, Mukherjee S, Kahn AR, Stewart AL, Logan DJ, Negri JM, Duvet M, Jaras M, Puram R, Dancik V, Al-Shahrour F, Kindler T, Tothova Z, Chattopadhyay S, Hasaka T, Narayan R, Dai M, Huang C, Shterental S, Chu LP, Haydu JE, Shieh JH, Steensma DP, Munoz B, Bittker JA, Shamji AF, Clemons PA, Tolliday NJ, Carpenter AE, Gilliland DG, Stern AM, Moore MA, Scadden DT, Schreiber SL, Ebert BL, Golub TR (2013) Niche-based screening identifies small-molecule inhibitors of leukemia stem cells. Nat Chem Biol 9(12):840–848. doi:10.1038/nchembio.1367

    Article  CAS  Google Scholar 

  14. Schulte J, Sepp KJ, Wu C, Hong P, Littleton JT (2011) High-content chemical and RNAi screens for suppressors of neurotoxicity in a Huntington’s disease model. PLoS One 6(8):e23841. doi:10.1371/journal.pone.0023841

    Article  CAS  Google Scholar 

  15. Shan J, Schwartz RE, Ross NT, Logan DJ, Thomas D, Duncan SA, North TE, Goessling W, Carpenter AE, Bhatia SN (2013) Identification of small molecules for human hepatocyte expansion and iPS differentiation. Nat Chem Biol 9(8):514–520. doi:10.1038/nchembio.1270

    Article  CAS  Google Scholar 

  16. Nishiya N, Oku Y, Kumagai Y, Sato Y, Yamaguchi E, Sasaki A, Shoji M, Ohnishi Y, Okamoto H, Uehara Y (2014) A zebrafish chemical suppressor screening identifies small molecule inhibitors of the Wnt/beta-catenin pathway. Chem Biol 21(4):530–540. doi:10.1016/j.chembiol.2014.02.015

    Article  CAS  Google Scholar 

  17. Taylor KL, Grant NJ, Temperley ND, Patton EE (2010) Small molecule screening in zebrafish: an in vivo approach to identifying new chemical tools and drug leads. Cell Commun Signal 8:11. doi:10.1186/1478-811X-8-11

    Article  Google Scholar 

  18. Reisen F, Sauty de Chalon A, Pfeifer M, Zhang X, Gabriel D, Selzer P (2015) Linking phenotypes and modes of action through high-content screen fingerprints. Assay Drug Dev Technol 13(7):415–427. doi:10.1089/adt.2015.656

    Article  CAS  Google Scholar 

  19. Sundaramurthy V, Barsacchi R, Chernykh M, Stoter M, Tomschke N, Bickle M, Kalaidzidis Y, Zerial M (2014) Deducing the mechanism of action of compounds identified in phenotypic screens by integrating their multiparametric profiles with a reference genetic screen. Nat Protoc 9(2):474–490. doi:10.1038/nprot.2014.027

    Article  CAS  Google Scholar 

  20. Sutherland JJ, Low J, Blosser W, Dowless M, Engler TA, Stancato LF (2011) A robust high-content imaging approach for probing the mechanism of action and phenotypic outcomes of cell-cycle modulators. Mol Cancer Ther 10(2):242–254. doi:10.1158/1535-7163.MCT-10-0720

    Article  CAS  Google Scholar 

  21. Gibson CC, Zhu W, Davis CT, Bowman-Kirigin JA, Chan AC, Ling J, Walker AE, Goitre L, Delle Monache S, Retta SF, Shiu YT, Grossmann AH, Thomas KR, Donato AJ, Lesniewski LA, Whitehead KJ, Li DY (2015) Strategy for identifying repurposed drugs for the treatment of cerebral cavernous malformation. Circulation 131(3):289–299. doi:10.1161/CIRCULATIONAHA.114.010403

    Article  CAS  Google Scholar 

  22. Gustafsdottir SM, Ljosa V, Sokolnicki KL, Anthony Wilson J, Walpita D, Kemp MM, Petri Seiler K, Carrel HA, Golub TR, Schreiber SL, Clemons PA, Carpenter AE, Shamji AF (2013) Multiplex cytological profiling assay to measure diverse cellular states. PLoS One 8(12):e80999. doi:10.1371/journal.pone.0080999

    Article  Google Scholar 

  23. Singh S, Carpenter AE, Genovesio A (2014) Increasing the content of high-content screening: an overview. J Biomol Screen 19(5):640–650. doi:10.1177/1087057114528537

    Article  Google Scholar 

  24. Halder V, Kombrink E (2015) Facile high-throughput forward chemical genetic screening by in situ monitoring of glucuronidase-based reporter gene expression in Arabidopsis thaliana. Front Plant Sci 6:13. doi:10.3389/fpls.2015.00013

    Article  Google Scholar 

  25. Allan C, Burel JM, Moore J, Blackburn C, Linkert M, Loynton S, Macdonald D, Moore WJ, Neves C, Patterson A, Porter M, Tarkowska A, Loranger B, Avondo J, Lagerstedt I, Lianas L, Leo S, Hands K, Hay RT, Patwardhan A, Best C, Kleywegt GJ, Zanetti G, Swedlow JR (2012) OMERO: flexible, model-driven data management for experimental biology. Nat Methods 9(3):245–253. doi:10.1038/nmeth.1896

    Article  CAS  Google Scholar 

  26. Adler J, Parmryd I (2010) Quantifying colocalization by correlation: the Pearson correlation coefficient is superior to the Mander’s overlap coefficient. Cytometry A 77(8):733–742. doi:10.1002/cyto.a.20896

    Article  Google Scholar 

  27. Vincent L (1993) Morphological grayscale reconstruction in image analysis: applications and efficient algorithms. IEEE Trans Image Process 2(2):176–201. doi:10.1109/83.217222

    Article  CAS  Google Scholar 

  28. Kamentsky L, Jones TR, Fraser A, Bray MA, Logan DJ, Madden KL, Ljosa V, Rueden C, Eliceiri KW, Carpenter AE (2011) Improved structure, function and compatibility for Cell Profiler: modular high-throughput image analysis software. Bioinformatics 27(8):1179–1180. doi:10.1093/bioinformatics/btr095

    Article  CAS  Google Scholar 

  29. Tiscornia G, Singer O, Verma IM (2006) Production and purification of lentiviral vectors. Nat Protoc 1(1):241–245. doi:10.1038/nprot.2006.37

    Article  CAS  Google Scholar 

  30. Chung N, Zhang XD, Kreamer A, Locco L, Kuan PF, Bartz S, Linsley PS, Ferrer M, Strulovici B (2008) Median absolute deviation to improve hit selection for genome-scale RNAi screens. J Biomol Screen 13(2):149–158. doi:10.1177/1087057107312035

    Article  CAS  Google Scholar 

  31. Konig R, Chiang CY, Tu BP, Yan SF, DeJesus PD, Romero A, Bergauer T, Orth A, Krueger U, Zhou Y, Chanda SK (2007) A probability-based approach for the analysis of large-scale RNAi screens. Nat Methods 4(10):847–849. doi:10.1038/nmeth1089

    Article  Google Scholar 

  32. Sigoillot FD, King RW (2011) Vigilance and validation: keys to success in RNAi screening. ACS Chem Biol 6(1):47–60. doi:10.1021/cb100358f

    Article  CAS  Google Scholar 

  33. Kim JH, Lee SR, Li LH, Park HJ, Park JH, Lee KY, Kim MK, Shin BA, Choi SY (2011) High cleavage efficiency of a 2A peptide derived from porcine teschovirus-1 in human cell lines, zebrafish and mice. PLoS One 6(4):e18556. doi:10.1371/journal.pone.0018556

    Article  CAS  Google Scholar 

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Acknowledgements

We would like to thank Madhu Lal-Nag for assistance with image retrieval. This work was supported by the Intramural Research Program of the NIH, NINDS and the Trans-NIH RNAi initiative.

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Authors and Affiliations

  1. National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA

    Samuel A. Hasson

  2. Biogen, Cambridge, MA, 02142, USA

    Adam I. Fogel

  3. Department of Discovery Oncology Genentech Inc., South San Francisco, CA, 94080, USA

    Scott E. Martin

  4. Pfizer, Inc., 610 Main Street, Cambridge, MA, 02144, USA

    Samuel A. Hasson

Authors
  1. Adam I. Fogel
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  2. Scott E. Martin
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  3. Samuel A. Hasson
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Corresponding author

Correspondence to Samuel A. Hasson .

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Editors and Affiliations

  1. Epizyme, Inc., Cambridge, Massachusetts, USA

    William P. Janzen

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© 2016 Springer Science+Business Media New York

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Fogel, A.I., Martin, S.E., Hasson, S.A. (2016). Application of Imaging-Based Assays in Microplate Formats for High-Content Screening. In: Janzen, W. (eds) High Throughput Screening. Methods in Molecular Biology, vol 1439. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3673-1_18

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  • DOI: https://doi.org/10.1007/978-1-4939-3673-1_18

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3671-7

  • Online ISBN: 978-1-4939-3673-1

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