title: Protocols and programs for high-throughput growth and aging phenotyping in yeast.
abstract: In microorganisms, and more particularly in yeasts, a standard phenotyping approach consists in the analysis of fitness by growth rate determination in different conditions. One growth assay that combines high throughput with high resolution involves the generation of growth curves from 96-well plate microcultivations in thermostated and shaking plate readers. To push the throughput of this method to the next level, we have adapted it in this study to the use of 384-well plates. The values of the extracted growth parameters (lag time, doubling time and yield of biomass) correlated well between experiments carried out in 384-well plates as compared to 96-well plates or batch cultures, validating the higher-throughput approach for phenotypic screens. The method is not restricted to the use of the budding yeast Saccharomyces cerevisiae, as shown by consistent results for other species selected from the Hemiascomycete class. Furthermore, we used the 384-well plate microcultivations to develop and validate a higher-throughput assay for yeast Chronological Life Span (CLS), a parameter that is still commonly determined by a cumbersome method based on counting "Colony Forming Units". To accelerate analysis of the large datasets generated by the described growth and aging assays, we developed the freely available software tools GATHODE and CATHODE. These tools allow for semi-automatic determination of growth parameters and CLS behavior from typical plate reader output files. The described protocols and programs will increase the time- and cost-efficiency of a number of yeast-based systems genetics experiments as well as various types of screens.
authors.affiliation: Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
authors.forename: Paul P
authors.initials: PP
authors.lastname: Jung
authors.affiliation: Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
authors.forename: Nils
authors.initials: N
authors.lastname: Christian
authors.affiliation: Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
authors.forename: Daniel P
authors.initials: DP
authors.lastname: Kay
authors.affiliation: Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; National Center for Microscopy and Imaging Research, University of California San Diego, La Jolla, California, United States of America.
authors.forename: Alexander
authors.initials: A
authors.lastname: Skupin
authors.affiliation: Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
authors.forename: Carole L
authors.initials: CL
authors.lastname: Linster
mesh_terms: D001203:Ascomycota / Q000254:growth & development; D018533:Biomass; D057166:High-Throughput Screening Assays / Q000379:methods* / Q000706:statistics & numerical data; D007700:Kinetics; D009172:Mycology / Q000379:methods / Q000706:statistics & numerical data; D010641:Phenotype; D012441:Saccharomyces cerevisiae / Q000254:growth & development; D054712:Salinity; D012984:Software; D015003:Yeasts / Q000254:growth & development*
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