Stress response and adaptation in fungi.
I have always been fascinated by the fact that life on earth, based on nearly identical sets of chemical reactions for all organisms, can function in such diverse environments.
The general topic of our research are the responses to environmental changes in fungi. There are direct effects of the change on yeast physiology and cellular makeup, and there is an adaptive response which, ideally, helps the organism resume growth under the changed conditions. We ask what the effect of the change is on biology, and how the adaptie response affects cellular functioning.
Of particular interest are environmental conditions encountered by the fungi (yeasts and filamentous fungi) in food, in industrial production conditions, and in disease. As many of these conditions also affect central intracellular or metabolic parameters such as energy or intracellular pH, these have had our particular attention.
For a long time, it was thought that it was crucial for cells to maintian a constant, neutral pHi. This is because almost all the molecules in cells are either acids or bases, and therefore their charge and interaction properties would change with changing pH. We have found, using the pH sensitive GFP rationmetric pHluorin, that pH in yeast is far from constant, and that changes in pH function as a signal to control cellular growth, transcription, and signal transduction. We are currently investigating how pH interacts with the central pathways for nutrient signalling, Ras-PKA and TOR, and how this effects growth, stress tolerance and survival.
Orij R, Urbanus M, Vizeacoumar F, Giaever G, Boone C, Nislow C, Brul S, and Smits GJ . 2012 . Genome-wide analysis of intracellular pH reveals quantitative control of cell division rate by pHc in Saccharomyces cerevisiae . Genome Biol. 13 :R80
Additional file 1 : All mutants with deviating pHc at various pHex, and during respiratory growth. Mutants with aberrant pHc under the standard condition (glucose, pH 5.0) were subjected to growth in pH 3.0, 7.5, as well as 2% ethanol/2% glycerol pH 5.0. Mutants were pre-grown overnight under standard conditions except for the 2% ethanol/2% glycerol experiment, in which case mutants were pre-grown in 2% ethanol/2% glycerol because of the long adaptation time to nonfermentable carbon source conditions. Cells were re-inoculated in described conditions and grown for 4 hours prior to measurements. Mutants were measured at least six timesat pH 5.0and at least three times in all other conditions. Mutants with significantly low pHc in any condition are indicated in orange, while mutants with significantly high pHc are indicated in blue.
Additional file 2 : pHc analysis of 432 slow growing mutants. All strains were grown in standard conditions (2% glucose, pHex of 5.0) and fluorescence was registered in three to six biological replicates, and are presented as average and 95% confidence interval. pHc was compared to wild-type (WT) controls in the same replicate, to determine a Z-value. Significance of the pHc difference with WT was determined using a two-tailed t-test assuming equal variance with a P-value < 0.05. ND refers to mutants for which fewer than three replicates were successfully measured. Significantly low pHc values are shown in orange, significantly high pHc values in blue.
Additional file 3 : Classification of mutants. Mutants are classified as having a growth rate-pHc relationship similar to wild type (WT; no significant deviation from the predicted growth rate based on pHc-growth rate relationship of the parent strain, low growth rate/pHc (significant positive deviation from the parent fit), or high growth rate/pHc (significant negative deviation from the parent fit), and are categorized according to functional classification.
Additional file 4 : Figures S1 to S4. See Additional file 5 for further data pertaining to Figure S3.
Additional file 5 : Data belonging to the hierarchical cluster plot in Figure S3 in Additional file 4. Mutants are listed in the order in which they appear in the cluster plot, for all three clusters. Mutant growth profiles were fitted to the parent strain pHc-growth rate relationship, and at each time point the Z-value of the digression from the fit was determined compared to the average and variance of 96 parent strain growth curves at the same time point. Time courses during the growth phase (t = 4 h to t = 9 h) of these Z-values were usedtostatistically categorize the mutants as wild type (WT; 92/173 mutants; 96 parent strain profiles also fall in this category), significantly (corrected P-value <0.01) slow growing (62/173 mutants), or significantly fast growing (19/173 mutants) with respect to pHc.
Zakrzewska A, van Eikenhorst G , Burggraaff JEC , Vis DJ, Hoefsloot H, Delneri D, Oliver SG, Brul S, Smits GJ. 2011. Genome-wide analysis of yeast stress survival and tolerance acquisition to analyze the central trade-off between growth rate and cellular robustness. Mol. Biol. Cell, 22 :4435-4446
Log transformations of viability percentages without and with growth rate correction.
All direct log transformed viability values of normal and heat pretreated samples are listed in "log transformed viability". All growth rate corrected log transformed viabilities are listed in "viability after growth rate cor". The non-pretreated viabiliy was corrected for growth rate at 30oC, the pretreated viability for growth rate at 38oC, and the acquired tolerance for the change in growth rate.
Each microarray dataset (separated for UPtag sense, UPtag antisense, DOWNtag sense and DOWNtag antisense) was background subtracted. Fractional intensities after 24 hours of growth (FI24) foreach tag werecorrected for the growth rate of the mutant to which it belongs, leading to the FI0. These values were normalized for the used for DNA isolation.
In the table these normalized FI0 values were used to calculate viability based on each tag independently. For instance,for mutant yal004w the strain abundance after severe oxidative stress (oxi 30oC) was determined using duplicate measurement of both sense and antisense UPtags, relative to the abundance of the strain in the growing culture). For each strain outlier values (p <0.0001) were removed. These individual ratios were averaged and multiplied by the population survival (in the case of severe oxidative stress in non-pretreated cultures 13%) to determine the survival of each individual strain (in the case of yal004w 9.9%).
Supplemental data accompanying Zakrzewska et al., OMICS , 14 :350-360