Systematic High-Content Screening of Fluorescently Tagged Yeast Double Mutant Strains.
Double mutants
Genetic interactions
High-content screening
Proteome-wide changes
Subcellular morphology
Yeast
Journal
Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969
Informations de publication
Date de publication:
2021
2021
Historique:
entrez:
30
9
2021
pubmed:
1
10
2021
medline:
6
1
2022
Statut:
ppublish
Résumé
We describe a protocol for high-content screening in budding yeast that can be used to study genetic interactions from a cell biological perspective. This approach can be used to map genetic interactions by monitoring one or more subcellular fluorescent markers of interest. In this case, changes in the morphology or abundance of a subcellular compartment, pathway or bioprocess are monitored in the background of a systematic array of yeast double mutants. Alternatively, the protocol can be used to monitor proteome-wide abundance and localization changes in a double mutant of interest by screening the yeast ORF-GFP collection. The protocol can be readily adapted for high-content screening of triple mutants, other large-scale yeast collections or expanded to screening of multiple growth conditions.
Identifiants
pubmed: 34590270
doi: 10.1007/978-1-0716-1740-3_3
doi:
Substances chimiques
Proteome
0
Saccharomyces cerevisiae Proteins
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
57-78Informations de copyright
© 2021. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
Références
Costanzo M, Kuzmin E, van Leeuwen J et al (2019) Global genetic networks and the genotype-to-phenotype relationship. Cell 177(1):85–100. https://doi.org/10.1016/j.cell.2019.01.033
doi: 10.1016/j.cell.2019.01.033
pubmed: 30901552
Costanzo M, VanderSluis B, Koch EN et al (2016) A global genetic interaction network maps a wiring diagram of cellular function. Science 353(6306):aaf1420. https://doi.org/10.1126/science.aaf1420
doi: 10.1126/science.aaf1420
pubmed: 27708008
pmcid: 5661885
van Leeuwen J, Pons C, Mellor JC et al (2016) Exploring genetic suppression interactions on a global scale. Science 354(6312):aag0839. https://doi.org/10.1126/science.aag0839
doi: 10.1126/science.aag0839
pubmed: 27811238
pmcid: 5562937
Li Z, Vizeacoumar FJ, Bahr S et al (2011) Systematic exploration of essential yeast gene function with temperature-sensitive mutants. Nat Biotechnol 29(4):361–367. https://doi.org/10.1038/nbt.1832
doi: 10.1038/nbt.1832
pubmed: 21441928
pmcid: 3286520
Adames NR, Gallegos JE, Peccoud J (2019) Yeast genetic interaction screens in the age of CRISPR/Cas. Curr Genet 65(2):307–327. https://doi.org/10.1007/s00294-018-0887-8
doi: 10.1007/s00294-018-0887-8
pubmed: 30255296
Boutros M, Heigwer F, Laufer C (2015) Microscopy-based high-content screening. Cell 163(6):1314–1325. https://doi.org/10.1016/j.cell.2015.11.007
doi: 10.1016/j.cell.2015.11.007
pubmed: 26638068
Mattiazzi Usaj M, Sahin N, Friesen H et al (2020) Systematic genetics and single-cell imaging reveal widespread morphological pleiotropy and cell-to-cell variability. Mol Syst Biol 16(2):e9243. https://doi.org/10.15252/msb.20199243
doi: 10.15252/msb.20199243
pubmed: 32064787
pmcid: 7025093
Mattiazzi Usaj M, Styles EB, Verster AJ et al (2016) High-content screening for quantitative cell biology. Trends Cell Biol 26(8):598–611. https://doi.org/10.1016/j.tcb.2016.03.008
doi: 10.1016/j.tcb.2016.03.008
pubmed: 27118708
Giaever G, Chu AM, Ni L et al (2002) Functional profiling of the Saccharomyces cerevisiae genome. Nature 418(6896):387–391. https://doi.org/10.1038/nature00935
doi: 10.1038/nature00935
pubmed: 12140549
Huh WK, Falvo JV, Gerke LC et al (2003) Global analysis of protein localization in budding yeast. Nature 425(6959):686–691. https://doi.org/10.1038/nature02026
doi: 10.1038/nature02026
pubmed: 14562095
Tong AH, Boone C (2006) Synthetic genetic array analysis in Saccharomyces cerevisiae. Methods Mol Biol 313:171–192
pubmed: 16118434
Kuzmin E, Sharifpoor S, Baryshnikova A et al (2014) Synthetic genetic array analysis for global mapping of genetic networks in yeast. Methods Mol Biol 1205:143–168. https://doi.org/10.1007/978-1-4939-1363-3_10
doi: 10.1007/978-1-4939-1363-3_10
pubmed: 25213244
Caicedo JC, Cooper S, Heigwer F et al (2017) Data-analysis strategies for image-based cell profiling. Nat Methods 14(9):849–863. https://doi.org/10.1038/nmeth.4397
doi: 10.1038/nmeth.4397
pubmed: 28858338
pmcid: 6871000
Grys BT, Lo DS, Sahin N et al (2017) Machine learning and computer vision approaches for phenotypic profiling. J Cell Biol 216(1):65–71. https://doi.org/10.1083/jcb.201610026
doi: 10.1083/jcb.201610026
pubmed: 27940887
pmcid: 5223612
Caicedo JC, Roth J, Goodman A et al (2019) Evaluation of deep learning strategies for nucleus segmentation in fluorescence images. Cytometry A 95(9):952–965. https://doi.org/10.1002/cyto.a.23863
doi: 10.1002/cyto.a.23863
pubmed: 31313519
pmcid: 6771982
Moen E, Bannon D, Kudo T et al (2019) Deep learning for cellular image analysis. Nat Methods 16(12):1233–1246. https://doi.org/10.1038/s41592-019-0403-1
doi: 10.1038/s41592-019-0403-1
pubmed: 31133758
Smith K, Piccinini F, Balassa T et al (2018) Phenotypic image analysis software tools for exploring and understanding big image data from cell-based assays. Cell Syst 6(6):636–653. https://doi.org/10.1016/j.cels.2018.06.001
doi: 10.1016/j.cels.2018.06.001
pubmed: 29953863
Bray MA, Carpenter AE (2018) Quality control for high-throughput imaging experiments using machine learning in Cellprofiler. Methods Mol Biol 1683:89–112. https://doi.org/10.1007/978-1-4939-7357-6_7
doi: 10.1007/978-1-4939-7357-6_7
pubmed: 29082489
pmcid: 6112602
Costanzo M, Baryshnikova A, Bellay J et al (2010) The genetic landscape of a cell. Science 327(5964):425–431. https://doi.org/10.1126/science.1180823
doi: 10.1126/science.1180823
pubmed: 20093466
pmcid: 5600254
Fischer B, Sandmann T, Horn T et al (2015) A map of directional genetic interactions in a metazoan cell. Elife 4:e05464. https://doi.org/10.7554/eLife.05464
doi: 10.7554/eLife.05464
pmcid: 4384530
Laufer C, Fischer B, Billmann M et al (2013) Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping. Nat Methods 10(5):427–431. https://doi.org/10.1038/nmeth.2436
doi: 10.1038/nmeth.2436
pubmed: 23563794
Styles EB, Founk KJ, Zamparo LA et al (2016) Exploring quantitative yeast Phenomics with single-cell analysis of DNA damage foci. Cell Syst 3(3):264–277. e210. https://doi.org/10.1016/j.cels.2016.08.008
doi: 10.1016/j.cels.2016.08.008
pubmed: 27617677
pmcid: 5689480
Vizeacoumar FJ, van Dyk N, Vizeacoumar FS et al (2010) Integrating high-throughput genetic interaction mapping and high-content screening to explore yeast spindle morphogenesis. J Cell Biol 188(1):69–81. https://doi.org/10.1083/jcb.200909013
doi: 10.1083/jcb.200909013
pubmed: 20065090
pmcid: 2812844
Breslow DK, Cameron DM, Collins SR et al (2008) A comprehensive strategy enabling high-resolution functional analysis of the yeast genome. Nat Methods 5(8):711–718. https://doi.org/10.1038/nmeth.1234
doi: 10.1038/nmeth.1234
pubmed: 18622397
pmcid: 2756093
Schuldiner M, Collins SR, Thompson NJ et al (2005) Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell 123(3):507–519. https://doi.org/10.1016/j.cell.2005.08.031
doi: 10.1016/j.cell.2005.08.031
pubmed: 16269340
Hu Y, Rolfs A, Bhullar B et al (2007) Approaching a complete repository of sequence-verified protein-encoding clones for Saccharomyces cerevisiae. Genome Res 17(4):536–543. https://doi.org/10.1101/gr.6037607
doi: 10.1101/gr.6037607
pubmed: 17322287
pmcid: 1832101
Gelperin DM, White MA, Wilkinson ML et al (2005) Biochemical and genetic analysis of the yeast proteome with a movable ORF collection. Genes Dev 19(23):2816–2826. https://doi.org/10.1101/gad.1362105
doi: 10.1101/gad.1362105
pubmed: 16322557
pmcid: 1315389
Meurer M, Duan Y, Sass E et al (2018) Genome-wide C-SWAT library for high-throughput yeast genome tagging. Nat Methods 15(8):598–600. https://doi.org/10.1038/s41592-018-0045-8
doi: 10.1038/s41592-018-0045-8
pubmed: 29988096
Weill U, Yofe I, Sass E et al (2018) Genome-wide SWAp-Tag yeast libraries for proteome exploration. Nat Methods 15(8):617–622. https://doi.org/10.1038/s41592-018-0044-9
doi: 10.1038/s41592-018-0044-9
pubmed: 29988094
pmcid: 6076999
Khmelinskii A, Blaszczak E, Pantazopoulou M et al (2014) Protein quality control at the inner nuclear membrane. Nature 516(7531):410–413. https://doi.org/10.1038/nature14096
doi: 10.1038/nature14096
pubmed: 25519137
pmcid: 4493439