Quantitative analysis of yeast gene function using competition experiments in continuous culture

Baganz, Frank; Hayes, Andrew; Farquhar, Ronnie; Butler, Philip R.; Gardner, David C.; Oliver, Stephen G.

doi:10.1002/(sici)1097-0061(199811)14:15<1417::aid-yea334>3.3.co;2-e

Cited by 11 publications

(16 citation statements)

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“…FY2 is the strain from which the BY strain series 14 , and hence the strain from which the complete knockout collection 15 , was derived. YSBN1 and YSBN2 are prototrophic strains that carry drug resistance markers inserted into their genomes at a phenotypically neutral site 16,17 . Besides the two diploid strains, a set of haploid strains with the two different mating types was also constructed (Supplementary Table S1).…”

Section: Resultsmentioning

confidence: 99%

Integrated multilaboratory systems biology reveals differences in protein metabolism between two reference yeast strains

et al. 2010

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The field of systems biology is often held back by difficulties in obtaining comprehensive, highquality, quantitative data sets. In this paper, we undertook an interlaboratory effort to generate such a data set for a very large number of cellular components in the yeast Saccharomyces cerevisiae, a widely used model organism that is also used in the production of fuels, chemicals, food ingredients and pharmaceuticals. With the current focus on biofuels and sustainability, there is much interest in harnessing this species as a general cell factory. In this study, we characterized two yeast strains, under two standard growth conditions. We ensured the high quality of the experimental data by evaluating a wide range of sampling and analytical techniques. Here we show significant differences in the maximum specific growth rate and biomass yield between the two strains. on the basis of the integrated analysis of the highthroughput data, we hypothesize that differences in phenotype are due to differences in protein metabolism.

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Section: Resultsmentioning

confidence: 99%

Integrated multilaboratory systems biology reveals differences in protein metabolism between two reference yeast strains

et al. 2010

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“…Yeast were grown in glucose-limited chemostat culture as described previously (10) in a medium (Table I) containing 100 mg/liter DL-[ 2 H 10 ]leucine (98.5 atom % excess) at a dilution rate of 0.1 h Ϫ1 . After a minimum of seven doubling times, sufficient to ensure that cells were fully labeled, unlabeled L-leucine (1 g in 50 ml) was added, and the incoming medium was changed to one containing unlabeled L-leucine at 50 mg/liter.…”

Section: Methodsmentioning

confidence: 99%

Dynamics of Protein Turnover, a Missing Dimension in Proteomics

Pratt

Petty

Riba-Garcia

et al. 2002

Molecular & Cellular Proteomics

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Functional genomic experiments frequently involve a comparison of the levels of gene expression between two or more genetic, developmental, or physiological states. Such comparisons can be carried out at either the RNA (transcriptome) or protein (proteome) level, but there is often a lack of congruence between parallel analyses using these two approaches. To fully interpret protein abundance data from proteomic experiments, it is necessary to understand the contributions made by the opposing processes of synthesis and degradation to the transition between the states compared. Thus, there is a need for reliable methods to determine the rates of turnover of individual proteins at amounts comparable to those obtained in proteomic experiments. Here, we show that stable isotope-labeled amino acids can be used to define the rate of breakdown of individual proteins by inspection of mass shifts in tryptic fragments. The approach has been applied to an analysis of abundant proteins in glucoselimited yeast cells grown in aerobic chemostat culture at steady state. The average rate of degradation of 50 proteins was 2.2%/h, although some proteins were turned over at imperceptible rates, and others had degradation rates of almost 10%/h. This range of values suggests that protein turnover is a significant missing dimension in proteomic experiments and needs to be considered when assessing protein abundance data and comparing it to the relative abundance of cognate mRNA species.

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“…The precise control over growth rate also allows matching of growth rates between wild-type cultures and more slowly growing mutants, or among diverse strain backgrounds, by forcing the cells to grow at a steady state that is below the maximum growth rate of both (e.g., Hayes et al 2002;Torres et al 2007;Skelly et al 2013). Even small differences in competitive fitness can be accurately measured using the chemostat, making it a useful tool for characterizing individual mutants (Baganz et al 1998) and collections of strains (Delneri et al 2008).…”

Section: Continuous Culturementioning

confidence: 99%

Chemostat Culture for Yeast Physiology and Experimental Evolution

Dunham

Kerr

Miller

et al. 2017

Cold Spring Harb Protoc

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Continuous culture provides many benefits over the classical batch style of growing yeast cells. Steadystate cultures allow for precise control of growth rate and environment. Cultures can be propagated for weeks or months in these controlled environments, which is important for the study of experimental evolution. Despite these advantages, chemostats have not become a highly used system, in large part because of their historical impracticalities, including low throughput, large footprint, systematic complexity, commercial unavailability, high cost, and insufficient protocol availability. However, we have developed methods for building a relatively simple, low-cost, small footprint array of chemostats that can be run in multiples of 32. This "ministat array" can be applied to problems in yeast physiology and experimental evolution. BATCH CULTUREThe most common method of growing yeast cell cultures is the standard "batch" culture. In this regime, a small number of cells are inoculated into nutrient-rich medium and allowed to divide at maximal growth rate through nutrient exhaustion and into saturation. Sampling of the culture for the experiment of choice is most typically done from the saturated culture or from cells growing in midlog phase before the diauxic shift. Batch culture provides a number of obvious benefits-it is easy, uses glassware commonly available in any laboratory, and is consistent with a vast literature. However, batch cultures can be problematic for certain applications. When comparing cells of different genotypes, for example, differences in the maximal growth rate are a common phenotype. Many other phenotypes co-vary with growth rate, leading to a nonspecific suite of cell biological, gene expression, and other physiological changes that may not be directly related to the mutation of interest (Regenberg et al. 2006;Castrillo et al. 2007;Brauer et al. 2008).Batch culture has also been a standard for long-term evolution experiments. Depending on the question being asked, batch culture with serial dilution can be a simple and scalable solution (e.g., Zeyl et al. 2003;Lang et al. 2011). However, such cultures are only rarely propagated in a relatively constant environment and growth rate regime because doing so can require a heroic sampling regimen where back dilution is performed multiple times per day (e.g., Torres et al. 2010). More typically, cultures are allowed to exhaust nutrients before transfer to new medium, leading to a variation in growth rate and nutrient access over the evolutionary time course. These discontinuities in selective pressure can lead to complex subpopulation structures in which different genotypes specialize for the various stages of the growth cycle (e.g., dividing a few extra times or failing to die after saturation, shortening lag phase,

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Quantitative analysis of yeast gene function using competition experiments in continuous culture

Cited by 11 publications

References 0 publications

Integrated multilaboratory systems biology reveals differences in protein metabolism between two reference yeast strains

Integrated multilaboratory systems biology reveals differences in protein metabolism between two reference yeast strains

Dynamics of Protein Turnover, a Missing Dimension in Proteomics

Chemostat Culture for Yeast Physiology and Experimental Evolution

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