Measuring growth rate in high-throughput growth phenotyping

Current Opinion in Biotechnology

Volumn 22, Issue 1, 2011, Pages 94-102

  Blomberg, Anders ^a  

^a UNIVERSITY OF GOTHENBURG   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

BATCH EFFECT; FALSE DISCOVERY RATE; FUNCTIONAL GENOMICS; HIGH QUALITY; HIGH-THROUGHPUT; HIGH-THROUGHPUT MEASUREMENTS; INDIVIDUAL CELLS; LOW CORRELATION; PHENOTYPING; SYSTEMS BIOLOGY;

GROWTH RATE;

ACCURACY; AUTOMATION; CARBON SOURCE; CELL GROWTH; CELL PROLIFERATION; GROWTH RATE; HIGH THROUGHPUT SCREENING; INTRASPECIFIC COMPETITION; LIQUID CULTURE; MATHEMATICAL MODEL; NONHUMAN; OPTICAL DENSITY; PHENOTYPE; PREDICTION; PRIORITY JOURNAL; REPRODUCIBILITY; REVIEW; STANDARDIZATION; STRAIN DIFFERENCE; SYSTEMS BIOLOGY;

ARTIFACTS; CELL COUNT; CELL CULTURE TECHNIQUES; CELL PROLIFERATION; COLONY COUNT, MICROBIAL; HIGH-THROUGHPUT SCREENING ASSAYS; MATHEMATICAL COMPUTING; MICROBIOLOGICAL PHENOMENA; MOLECULAR PROBES; PHENOTYPE; SYSTEMS BIOLOGY;

EID: 79551526832     PISSN: 09581669     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.copbio.2010.10.013     Document Type: Review

References (63)

1. Warringer J., Ericson E., Fernandez L., Nerman O., Blomberg A. High-resolution yeast phenomics resolves different physiological features in the saline response. Proc Natl Acad Sci U S A 2003, 100:15724-15729.
2. Hillenmeyer M.E., Fung E., Wildenhain J., Pierce S.E., Hoon S., Lee W., Proctor M., St Onge R.P., Tyers M., Koller D., et al. The chemical genomic portrait of yeast: uncovering a phenotype for all genes. Science 2008, 320:362-365.
3. Castrillo J.I., Zeef L.A., Hoyle D.C., Zhang N., Hayes A., Gardner D.C., Cornell M.J., Petty J., Hakes L., Wardleworth L., et al. Growth control of the eukaryote cell: a systems biology study in yeast. J Biol 2007, 6:4.
4. Brauer M.J., Huttenhower C., Airoldi E.M., Rosenstein R., Matese J.C., Gresham D., Boer V.M., Troyanskaya O.G., Botstein D. Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast. Mol Biol Cell 2008, 19:352-367.
5. Lu C., Brauer M.J., Botstein D. Slow growth induces heat-shock resistance in normal and respiratory-deficient yeast. Mol Biol Cell 2009, 20:891-903.
6. King R.D., Rowland J., Oliver S.G., Young M., Aubrey W., Byrne E., Liakata M., Markham M., Pir P., Soldatova L.N., et al. The automation of science. Science 2009, 324:85-89.
7. Sparkes A., Aubrey W., Byrne E., Clare A., Khan M.N., Liakata M., Markham M., Rowland J., Soldatova L.N., Whelan K.E., et al. Towards robot scientists for autonomous scientific discovery. Autom Exp 2010, 2.
8. Warringer J., Anevski D., Liu B., Blomberg A. Chemogenetic fingerprinting by analysis of cellular growth dynamics. BMC Chem Biol 2008, 8.
9. Toussaint M., Conconi A. High-throughput and sensitive assay to measure yeast cell growth: A bench protocol for testing genotoxic agents. Nat Protoc 2006, 1:1922-1928.
10. Warringer J., Blomberg A. Automated screening in environmental arrays allows analysis of quantitative phenotypic profiles in saccharomyces cerevisiae. Yeast 2003, 20:53-67.
11. Kensy F., Engelbrecht C., Buchs J. Scale-up from microtiter plate to laboratory fermenter: evaluation by online monitoring techniques of growth and protein expression in escherichia coli and hansenula polymorpha fermentations. Microb Cell Fact 2009, 8.
12. Pylvanainen I: A parametric approach to yeast growth curve estimation and standardization. In: PhD. Chalmers University of Technology, Gothenburg, Sweden (2005).
13. Jasnos L., Korona R. Epistatic buffering of fitness loss in yeast double deletion strains. Nat Genet 2007, 39:550-554.
14. Toussaint M., Levasseur G., Gervais-Bird J., Wellinger R.J., Elela S.A., Conconi A. A high-throughput method to measure the sensitivity of yeast cells to genotoxic agents in liquid cultures. Mutat Res 2006, 606:92-105.
15. Buchs J. Introduction to advantages and problems of shaken cultures. Biochem Eng J 2001, 7:91-98.
16. Hermann R., Lehmann M., Buchs J. Characterization of gas-liquid mass transfer phenomena in microtiter plates. Biotechnol Bioeng 2003, 81:178-186.
17. Kensy F., Zang E., Faulhammer C., Tan R.K., Buchs J. Validation of a high-throughput fermentation system based on online monitoring of biomass and fluorescence in continuously shaken microtiter plates. Microb Cell Fact 2009, 8.
18. Samorski M., Muller-Newen G., Buchs J. Quasi-continuous combined scattered light and fluorescence measurements: a novel measurement technique for shaken microtiter plates. Biotechnol Bioeng 2005, 92:61-68.
19. Thatcher J.W., Shaw J.M., Dickinson W.J. Marginal fitness contributions of nonessential genes in yeast. Proc Natl Acad Sci U S A 1998, 95:253-257.
20. Giaever G., Chu A.M., Ni L., Connelly C., Riles L., Veronneau S., Dow S., Lucau-Danila A., Anderson K., Andre B., et al. Functional profiling of the saccharomyces cerevisiae genome. Nature 2002, 418:387-391.
21. Winzeler E.A., Lee B., McCusker J.H., Davis R.W. Whole genome genetic-typing in yeast using high-density oligonucleotide arrays. Parasitology 1999, 118(Suppl.):S73-80.
22. Deutschbauer A.M., Jaramillo D.F., Proctor M., Kumm J., Hillenmeyer M.E., Davis R.W., Nislow C., Giaever G. Mechanisms of haploinsufficiency revealed by genome-wide profiling in yeast. Genetics 2005, 169:1915-1925.
23. Breslow D.K., Cameron D.M., Collins S.R., Schuldiner M., Stewart-Ornstein J., Newman H.W., Braun S., Madhani H.D., Krogan N.J., Weissman J.S. A comprehensive strategy enabling high-resolution functional analysis of the yeast genome. Nat Methods 2008, 5:711-718.
24. Baryshnikova A, Costanzo M, Kim Y, Ding H, Koh J, Toufighi K, Youn J-Y, Ou J, San Luis B-J, Bandyopadhyay S, et al.: A genome-scale approach for quantitative analysis of fitness and genetic interactions in yeast. Nature Methods, in press.
25. Costanzo M., Baryshnikova A., Bellay J., Kim Y., Spear E.D., Sevier C.S., Ding H., Koh J.L., Toufighi K., Mostafavi S., et al. The genetic landscape of a cell. Science 2010, 327:425-431.
26. Collins S.R., Schuldiner M., Krogan N.J., Weissman J.S. A strategy for extracting and analyzing large-scale quantitative epistatic interaction data. Genome Biol 2006, 7:R63.
27. Shah N.A., Laws R.J., Wardman B., Zhao L.P., Hartman J.Lt. Accurate, precise modeling of cell proliferation kinetics from time-lapse imaging and automated image analysis of agar yeast culture arrays. BMC Syst Biol 2007, 1.
28. Lamprecht M.R., Sabatini D.M., Carpenter A.E. Cellprofiler: free, versatile software for automated biological image analysis. Biotechniques 2007, 42:71-75.
29. Lawless C., Wilkinson D.J., Young A., Addinall S.G., Lydall D.A. Colonyzer: automated quantification of micro-organism growth characteristics on solid agar. BMC Bioinformatics 2010, 11:287.
30. Dittmar J.C., Reid R.J., Rothstein R. Screenmill: a freely available software suite for growth measurement, analysis and visualization of high-throughput screen data. BMC Bioinformatics 2010, 11:353.
31. Hartman J.Lt., Tippery N.P. Systematic quantification of gene interactions by phenotypic array analysis. Genome Biol 2004, 5:R49.
32. Bean J.M., Siggia E.D., Cross F.R. Coherence and timing of cell cycle start examined at single-cell resolution. Mol Cell 2006, 21:3-14.
33. Di Talia S., Skotheim J.M., Bean J.M., Siggia E.D., Cross F.R. The effects of molecular noise and size control on variability in the budding yeast cell cycle. Nature 2007, 448:947-951.
34. Godin M., Delgado F.F., Son S., Grover W.H., Bryan A.K., Tzur A., Jorgensen P., Payer K., Grossman A.D., Kirschner M.W., Manalis S.R. Using buoyant mass to measure the growth of single cells. Nat Methods 2010, 7:387-390.
35. Airoldi E.M., Huttenhower C., Gresham D., Lu C., Caudy A.A., Dunham M.J., Broach J.R., Botstein D., Troyanskaya O.G. Predicting cellular growth from gene expression signatures. PLoS Comput Biol 2009, 5:e1000257.
36. Boer V.M., Crutchfield C.A., Bradley P.H., Botstein D., Rabinowitz J.D. Growth-limiting intracellular metabolites in yeast growing under diverse nutrient limitations. Mol Biol Cell 2010, 21:198-211.
37. Makarenkov V., Zentilli P., Kevorkov D., Gagarin A., Malo N., Nadon R. An efficient method for the detection and elimination of systematic error in high-throughput screening. Bioinformatics 2007, 23:1648-1657.
38. Malo N., Hanley J.A., Carlile G., Liu J., Pelletier J., Thomas D., Nadon R. Experimental design and statistical methods for improved hit detection in high-throughput screening. J Biomol Screen 2010, 15:990-1000.
39. Malo N., Hanley J.A., Cerquozzi S., Pelletier J., Nadon R. Statistical practice in high-throughput screening data analysis. Nat Biotechnol 2006, 24:167-175.
40. Huber R., Palmen T.G., Ryk N., Hillmer A.K., Luft K., Kensy F., Buchs J. Replication methods and tools in high-throughput cultivation processes - recognizing potential variations of growth and product formation by on-line monitoring. BMC Biotechnol 2010, 10:22.
41. Jasnos L., Sliwa P., Korona R. Resolution and repeatability of phenotypic assays by automated growth curve analysis in yeast and bacteria. Anal Biochem 2005, 344:138-140.
42. Gribbon P., Lyons R., Laflin P., Bradley J., Chambers C., Williams B.S., Keighley W., Sewing A. Evaluating real-life high-throughput screening data. J Biomol Screen 2005, 10:99-107.
43. Brideau C., Gunter B., Pikounis B., Liaw A. Improved statistical methods for hit selection in high-throughput screening. J Biomol Screen 2003, 8:634-647.
44. Leek J.T., Scharpf R.B., Bravo H.C., Simcha D., Langmead B., Johnson W.E., Geman D., Baggerly K., Irizarry R.A. Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet 2010, 11:733-739.
45. Fudala A., Korona R. Low frequency of mutations with strongly deleterious but nonlethal fitness effects. Evolution 2009, 63:2164-2171.
46. Costanzo M.C., Skrzypek M.S., Nash R., Wong E., Binkley G., Engel S.R., Hitz B., Hong E.L., Cherry J.M. New mutant phenotype data curation system in the saccharomyces genome database. Database (Oxford) 2009, 2009. bap001.
47. Engel S.R., Balakrishnan R., Binkley G., Christie K.R., Costanzo M.C., Dwight S.S., Fisk D.G., Hirschman J.E., Hitz B.C., Hong E.L., et al. Saccharomyces genome database provides mutant phenotype data. Nucleic Acids Res 2009, 38(Database issue):D433-436.
48. Fernandez-Ricaud L., Warringer J., Ericson E., Glaab K., Davidsson P., Nilsson F., Kemp G.J., Nerman O., Blomberg A. Prophecy-a yeast phenome database, update 2006. Nucleic Acids Res 2007, 35(Database issue):D463-467.
49. Fernandez-Ricaud L, Warringer J, Ericson E, Pylvanainen I, Kemp GJ, Nerman O, Blomberg A: Prophecy-a database for high-resolution phenomics. Nucleic Acids Res 2005, 33(Database issue):D369-373.
50. Hampsey M. A review of phenotypes in saccharomyces cerevisiae. Yeast 1997, 13:1099-1133.
51. Vizeacoumar F.J., van Dyk N., Vizeacoumar F.S., Cheung V., Li J., Sydorskyy Y., Case N., Li Z., Datti A., Nislow C., et al. Integrating high-throughput genetic interaction mapping and high-content screening to explore yeast spindle morphogenesis. J Cell Biol 2010, 188:69-81.
52. Funke M., Buchenauer A., Schnakenberg U., Mokwa W., Diederichs S., Mertens A., Muller C., Kensy F., Buchs J. Microfluidic biolector-microfluidic bioprocess control in microtiter plates. Biotechnol Bioeng 2010, 107:497-505.
53. Orr H.A. Fitness and its role in evolutionary genetics. Nat Rev Genet 2009, 10:531-539.
54. Esguerra J., Warringer J., Blomberg A. Functional importance of individual rrna 2'-o-ribose methylations revealed by high-resolution phenotyping. RNA 2008, 14:649-656.
55. Krantz M., Ahmadpour D., Ottosson L.G., Warringer J., Waltermann C., Nordlander B., Klipp E., Blomberg A., Hohmann S., Kitano H. Robustness and fragility in the yeast high osmolarity glycerol (hog) signal-transduction pathway. Mol Syst Biol 2009, 5:281.
56. Liti G., Carter D.M., Moses A.M., Warringer J., Parts L., James S.A., Davey R.P., Roberts I.N., Burt A., Koufopanou V., et al. Population genomics of domestic and wild yeasts. Nature 2009, 458:337-341.
57. Österberg M., Kim H., Warringer J., Melen K., Blomberg A., von Heijne G. Phenotypic effects of membrane protein overexpression in saccharomyces cerevisiae. Proc Natl Acad Sci U S A 2006, 103:11148-11153.
58. Ericson E., Pylvanainen I., Fernandez-Ricaud L., Nerman O., Warringer J., Blomberg A. Genetic pleiotropy in saccharomyces cerevisiae quantified by high-resolution phenotypic profiling. Mol Genet Genomics 2006, 275:605-614.
59. Warringer J., Blomberg A. Involvement of yeast yol151w/gre2 in ergosterol metabolism. Yeast 2006, 23:389-398.
60. Jasnos L., Tomala K., Paczesniak D., Korona R. Interactions between stressful environment and gene deletions alleviate the expected average loss of fitness in yeast. Genetics 2008, 178:2105-2111.
61. Weiss A., Delproposto J., Giroux C.N. High-throughput phenotypic profiling of gene-environment interactions by quantitative growth curve analysis in saccharomyces cerevisiae. Anal Biochem 2004, 327:23-34.
62. Bochner B.R. New technologies to assess genotype-phenotype relationships. Nat Rev Genet 2003, 4:309-314.
63. Toussaint M., Wellinger R.J., Conconi A. Differential participation of homologous recombination and nucleotide excision repair in yeast survival to ultraviolet light radiation. Mutat Res 2010, 698:52-59.