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Keywords:

  • yeast;
  • ethanol stress;
  • osmotic stress;
  • yeast deletion collection

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

We quantified the growth behavior of all available single gene deletion strains of budding yeast under ethanol stress. Genome-wide analyses enabled the extraction of the genes and determination of the functional categories required for growth under this condition. Statistical analyses revealed that the growth of 446 deletion strains under stress induced by 8% ethanol was defective. We classified these deleted genes into known functional categories, and found that many were important for growth under ethanol stress including several categories that have not been characterized, such as peroxisome. We also performed genome-wide screening under osmotic stress and identified 329 osmotic-sensitive strains. We excluded these strains from the 446 ethanol-sensitive strains to extract the genes whose deletion caused sensitivity to ethanol-specific (359 genes), osmotic-specific (242 genes), and both stresses (87 genes). We also extracted the functional categories that are specifically important for growth under ethanol stress. The genes and functional categories identified in the analysis might provide clues to improving ethanol stress tolerance among yeast cells.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

The yeast Saccharomyces cerevisiae is used in the production of alcoholic beverages such as beer and wine, and its importance in the production of biofuels from biomass resources has recently increased. During bio-production processes, yeast cells are generally exposed to several types of environmental stresses that decrease their productivity, such as high ethanol concentrations, osmotic pressure, and oxidative stresses (Attfield, 1997; Gibson et al., 2007). Ethanol is a major stress factor that interferes with the growth and production of ethanol by yeast cells in the production process of alcoholic beverages and biofuels. Hence, the responses of yeast cells to ethanol have been investigated in detail in order to improve their tolerance to ethanol stress. For example, yeast cells respond to ethanol stress by altering the unsaturated fatty acid composition of the cellular membrane (You et al., 2003), accumulating trehalose (Lucero et al., 2000), selectively exporting mRNA from the nucleus (Takemura et al., 2004), and forming P-bodies (Izawa et al., 2007).

Studies of the genome-wide response to ethanol stress using microarrays and comprehensive expression data have resulted in the construction of some ethanol-tolerant yeast strains (Hirasawa et al., 2007). However, the construction of deletant or overexpression strains from those genes that are detected in transcriptional studies to alter their expression patterns in response to ethanol stress does not always lead to a change in the ethanol stress response. Thus, the effect of gene manipulation – such as deletion and overexpression – on the acquisition of ethanol tolerance in yeast cells remains obscure. Therefore, analysis of phenotypic changes such as sensitivity and tolerance to ethanol stress is important for improving the ethanol tolerance of yeast cells by genetic modifications.

Here, we report a high-resolution quantitative analysis of growth behavior under ethanol stress in a collection of yeast strains with a single gene deletion (Winzeler et al., 1999) to elucidate the functional categories of genes involved in survival under ethanol stress. This collection of strains is a powerful tool with which to determine the effects of gene deletion under specific conditions (Scherens & Goffeau, 2004). We cultured deletion strains individually with and without ethanol, and determined their growth curves to evaluate the effect of gene deletion. Other studies have screened genes that are important for growth under ethanol stress from collections of deletion strains (Kubota et al., 2004; Fujita et al., 2006; van Voorst et al., 2006); however, ethanol-sensitive strains were screened in these studies by colony formation on ethanol-supplemented agar, and their growth behavior was not quantified. In contrast, we quantified the specific growth rates of each deletion strain in a liquid medium with and without ethanol and statistically analyzed the effect of the gene deletion. In order to focus on genes that are involved in growth under stress, we excluded data for deletion strains with growth defects under nonstress conditions from further analysis. We also measured the growth of each strain under osmotic stress induced by adding NaCl to the medium. By comparing growth both under ethanol and under osmotic stresses, we identified which genes are generally important for the stress response and which are specifically important for either ethanol or osmotic stress. We screened novel genes and gene categories involved in growth under ethanol stress using high-throughput cultivation and statistical analysis.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Medium and yeast strains

We evaluated the growth of single gene deletion strains derived from S. cerevisiae BY4742 (MATαhis3Δ1 leu2Δ0 lys2Δ0 ura3Δ0) or BY4739 (MATαleu2Δ0 lys2Δ0 ura3Δ0) purchased from Open Biosystems. All strains were cultured in YPD medium (1% Bacto yeast extract, 2% Bacto peptone, and 2% glucose).

We prepared culture stocks by culturing deletion strains on plates containing YPD agar (YPD medium containing 2% agar) containing 150 μg mL−1 of geneticin. Colonies generated from each strain were suspended in 15% glycerol in 96-well microtiter plates and stored at −80 °C. Some deletion strains that proliferated slowly on the YPD plates with geneticin were removed; 4729 single gene deletion strains were eventually analyzed in this study.

Cultivation system of deletion strains in a microtiter plate

We prepared precultures by shaking deletion strains at 1050 strokes min−1 on a microplate shaker, TITRAMAX1000 (Heidolph Instruments, Germany), in 100 μL of YPD medium in 96-well microtiter plates (Corning Inc.) for 24 h at 30 °C. Thereafter, 2 μL of preculture was inoculated in 100 μL of warm YPD medium, and cells were cultured at 30 °C without shaking. To investigate the growth behavior of deletion strains under stress, 25 μL of 40% (v/v) ethanol (final concentration, 8%) or 25 μL of 5 M NaCl (final concentration, 1 M NaCl) was added to the culture medium 4 h later, at the time corresponding to the mid-log phase. Sterilized water (25 μL) was added to the culture medium to provide the nonstress condition. Growth of the deletion strains was monitored at 0, 2, 4, 5.5, 7, and 9 h under the nonstress condition and at 0, 2, 4, 7, 9, and 11 h under the stress condition by measuring the OD600 nm of each well using the microplate reader 1420 ARVO (PerkinElmer Inc.). Before measuring the OD, the plates were agitated for 1 min at 1050 strokes min−1 on a shaker. We used the HIS3 deletion strain of BY4742 (BY4742Δhis3) as a standard because the HIS3 deletion did not alter the phenotype from the wild-type strain BY4742. The standard strain was cultured together with the deletion strains (4 wells per plate). The standard strain was located at identical positions in all plates. A 96-well microtiter plate comprises eight rows and 12 columns. The standard strain was located at (3, 4), (3, 9), (6, 4), and (6, 9), where the values in parentheses represent the position (row, column) in a 96-well plate. We did not use the outermost wells of the 96-well plate, which are the first and eighth rows and the first and 12th columns in order to avoid the effect of evaporation of the medium. All strains were separately cultured twice under nonstress and stress conditions.

Calculation of specific growth rate

Raw OD data obtained by the microplate reader were processed as follows: the OD of blank wells containing only medium was subtracted from the raw OD data. Then, to compensate for the nonlinearity of the OD value in case of high cell density, ODs of several samples were measured both by the microplate reader and by the spectrophotometer, UVmini-1240 (Shimadzu Corporation, Japan), at 660 nm. Subsequently, we introduced the following relationships for the compensation of raw OD data of the microplate reader. We used different relationships before and after changing the environment because the culture volume was changed by the addition of ethanol, NaCl, or water. For data before the addition of ethanol, NaCl, or water, we used:

  • image

while for data after the addition of ethanol, NaCl, or water, we used:

  • image

where OD is the value obtained using the microplate reader and OD′ is the calibrated OD. The specific growth rate under the nonstress condition was calculated by linear regression using the natural logarithm of calibrated OD values at 5.5, 7, and 9 h, and that under the stress conditions was calculated using the natural logarithm of calibrated OD values at 7, 9, and 11 h. The robustness of the calculation of the specific growth rate using only three time points was confirmed by a good correlation between the specific growth rates obtained by three time points (7, 9, and 11 h under 8% ethanol) and a greater number of time points (7, 8, 9, 10, and 11 h under 8% ethanol) (data not shown). This indicated that the calculation of the growth rate using three time points was sufficiently accurate; therefore, we used three time points for calculating the specific growth rate.

To compare the specific growth rates of deletion strains cultured in different microtiter plates, specific growth rates were normalized with those of the standard strain cultured in each plate using the formula

  • image

where μi,j,k is the specific growth rate of strain i in plate j under condition k, inline imageis the average of the specific growth rate of the standard strain from four wells in plate j under condition k, μstd,k is the median of all specific growth rates of the standard strain under condition k, and inline image is the normalized specific growth rate. The normalized specific growth rates of all deletion strains under each condition are shown in Supporting Information, Table S1.

Functional analysis of gene products

Functions of gene products were classified using the Functional Catalogue (FunCat) described in the Munich Information Center for Protein Sequences (MIPS) database (http://mips.gsf.de/genre/proj/yeast/, Ruepp et al., 2004) and the Saccharomyces genome database (SGD, http://www.yeastgenome.org/). We applied a hypergeometric test to evaluate whether or not a functional category was overrepresented by genes deleted from strains exhibiting stress sensitivity by the following formula:

  • image

where N is the total number of genes, M is the number of genes related to a functional category from the total genes, n is the number of genes in the selected genes, and k is the number of genes related to a functional category from among the selected genes.

Randomization test

Ten thousand sets of randomized data were obtained by random sampling of the same number of the genes of ethanol-sensitive strains from the genes of all the deletion strains. Then the distributions of the proportion of each category in the randomized data sets were calculated and P-values of the observed data were computed by the two-sided hypothesis test with a normal distribution assumption.

Construction of single gene overexpression strains

For the construction of single gene overexpression strains LDB19, MEH1, PRO2, and YNL335W, the DNA fragment corresponding to each gene was amplified by a PCR from the BY4742Δhis3 genomic DNA using KOD plus DNA polymerase (Toyobo Co. Ltd, Japan) and the following sets of primers: 5′-TCACGGTACCATACGTTTTACCATG-3 and 5-AAATCTCGAGTAAATACCTTTAACG-3 for LDB19, 5-TAGTGGGTACCACGACAGATTTAAG-3 and 5-AGCTTCTAGACCAATGATGTTATAC-3 for MEH1, 5-GAGTAGGTACCAAAAGGAGCACAGG-3 and 5-ACGTCCTCTAGACATGGAACTTAGC-3 for PRO2, and 5-CTCCGGTACCAAAGAATCAATCATG-3 and 5-TGTTCATTCTAGACTCGCCTCATTG-3 for YNL335W (the underlined sequence represents the artificially introduced restriction enzyme sites for cloning into the expression vector). Each amplified PCR product was cloned into the appropriate restriction sites in the YIp-type vector pAURΔCENARS (Hirasawa et al., 2007). The sequence of each cloned gene was confirmed using the automated DNA sequencer ABI Prism 310 Genetic Analyzer (Applied Biosystems) and the BigDye Terminator Cycle Sequencing Kit v.3.1 (Applied Biosystems). The plasmids carrying each gene were introduced into the BY4742Δhis3 by the lithium acetate method (Gietz & Woods, 2002). In the constructed strains, the cloned genes were constitutively expressed from the ADH1 promoter on pAURΔCENARS.

Results and discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Identification of strains sensitive or tolerant to ethanol stress

To analyze the effects of single gene deletion on growth under ethanol and osmotic stress, we obtained growth data for all available single gene deletion strains of S. cerevisiae under nonstress and stress conditions. Stress conditions were created by the addition of ethanol (final concentration, 8%) or NaCl (final concentration, 1 M) to culture broth at the mid-log phase. We calculated the specific growth rates of strains under all culture conditions. Figure 1 shows that the measurement reproducibility of the specific growth rates of deletion strains was high.

image

Figure 1.  Reproducibility of culture experiments of all deletion strains under nonstress conditions. Correlation between specific growth rates of all deletion strains at first and second culture experiments. Horizontal and vertical axes represent specific growth rates under the nonstress condition in the first and second experiments, respectively. Each dot corresponds to a strain with a single gene deletion.

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We simultaneously obtained 720 sets of information regarding the specific growth rates of the standard strain from the cultivation of all the deletion strains in 90 microtiter plates twice under each condition. In each plate, the standard strain was contained in four wells. Table 1 shows the average and SD of the specific growth rates of 720 growth data for the standard strain under each condition. The coefficient of variance of the growth rate of the standard strain under the nonstress condition was 1%, indicating that the specific growth rates of deletion strains could be evaluated in our culture system at a high resolution.

Table 1.   Comparison of average values of specific growth rates of the standard strain and thresholds of specific growth rates to discern sensitive and tolerant deletion strains
ConditionAverage specific growth rate (h–1)SD (h–1)Threshold for sensitive strains (h–1)*Threshold for tolerant strains (h–1)*
  • *

    Thresholds were defined as average specific growth rate ± 3.3 SDs.

Nonstress0.4524.4 × 10–30.4370.466
8% Ethanol0.1785.6 × 10–30.1600.196
1 M NaCl0.2037.6 × 10–30.1780.229

From all the deletion strains available in the library, in order to identify those deletion strains that were tolerant or sensitive to stress, we statistically compared the specific growth rates of the deletion and standard strains. Because the distribution of the growth rates of the standard strain described above was bell shaped (Fig. 2), we applied the empirical rule that 99.9% of the data lay within 3.3 SD of the mean. Thus, deletion strains with growth rates outside the range of 3.3 SD of the mean could be regarded as stress tolerant or sensitive, with significantly different growth rates from the standard strain (P<0.001) (Fig. 2). We defined stress-sensitive deletion strains as those whose growth rates in both independent cultures were lower than the threshold value. Although the average growth rate of two cultures is generally used for such analyses, we used a conservative definition because the average growth rate is often unreliable when the data include outliers. Table 1 shows the threshold values of specific growth rates used to identify sensitive and tolerant strains under each condition.

image

Figure 2.  Identification of strains sensitive or tolerant to ethanol stress. The dashed line represents the frequency of specific growth rates of standard strain under ethanol stress; the solid line represents the frequency of all average specific growth rates of deletion strains under ethanol stress. Dashed–dotted lines represent thresholds of specific growth rates for judging ethanol-sensitive and -tolerant strains.

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Table 2 shows the numbers of stress-sensitive and -tolerant deletion strains under each condition. Some strains identified as stress sensitive also exhibited a significantly lower growth rate under the nonstress condition than that of the standard strain, as also reported by Warringer et al. (2003).

Table 2.   Numbers of deletion strains categorized by specific growth rates
 SensitiveNo changeTolerant
  1. Numbers in parentheses represent the number of deletion strains in each category not including those exhibiting growth defects under nonstress conditions.

Nonstress591 (0)4095 (4095)43 (43)
8% Ethanol864 (446)3862 (3690)3 (2)
1 M NaCl637 (329)4080 (3799)12 (10)

Comparison of data with those from other studies

We compared our data with the findings of others who have similarly examined the effect of a single gene deletion on growth under ethanol stress (Kubota et al., 2004; Fujita et al., 2006; van Voorst et al., 2006). Table 3 shows that our data overlapped with c. 70% of that from the ethanol-sensitive strains identified by others. The ethanol-sensitive strains identified in these studies included those with defective growth under the nonstress condition identified in the present study, as represented in parentheses in Table 3. Because in the present study we quantified the growth of individual strains, we could exclude deletion strains with defective growth under the nonstress condition and thus define the effect of a single gene deletion on the growth under stress more precisely. Thus, we excluded data from such strains from the following analyses to specifically determine which genes are required for growth under ethanol stress (Table 2). In the study reported by Warringer et al. (2003), the authors calculated the phenotype index by dividing the growth rate under the stress condition by that under the nonstress condition in order to take into consideration the growth defects due to the deletion. However, in this method, when a deletion strain exhibits severe growth defects in both the nonstress and the stress conditions, the calculated phenotype index often becomes large enough to be classified as a stress-tolerant strain. To exclude such cases, we removed the strains exhibiting growth defects in the nonstress condition from the analysis and used the specific growth rate itself for analysis.

Table 3.   Overlapping of published and present data regarding ethanol-sensitive strains
 No. of ethanol-sensitive strainsKubota et al. (2004)van Voorst et al. (2006)Fujita et al. (2006)Present study
  1. Numbers in parentheses represent the number of deletion strains not including those with growth defects under the non-stress condition identified in the present study.

Kubota et al. (2004)256 (114) 21 (5)61 (27)183 (63)
van Voorst et al. (2006)46 (20)  11 (5)38 (14)
Fujita et al. (2006)137 (56)   102 (33)
Present study864 (446)    

Among the other three studies, only four deletion strains of GIM4, GIM5, SMI1, and VPS36 were commonly observed to be sensitive to ethanol; these strains were also identified to be ethanol sensitive in the present study. Such a low overlap of the ethanol-sensitive strains among these studies could be due to the difference in the medium (liquid or solid) and the ethanol concentrations used. The deletion strains of GIM4 and GIM5 encoding the subunits of the heterohexameric cochaperone prefolding complex also exhibited growth defects under the nonstress condition in the present study; therefore, we consider that these genes are required not only for ethanol tolerance but also for normal growth. VPS36 encodes one of the components of the Endosomal Sorting Complex Required for Transport (ESCRT)-II. Notably, all the deletion strains of the genes encoding the components of ESCRT complexes –MVB12, SRN2, STP22, and VPS28 for ESCRT-I; SNF8 and VPS25 for ESCRT-II; and DID4, SNF7, and VPS24 for ESCRT-III – also exhibited sensitivity to ethanol. The ESCRT complex is involved in the mechanism of protein sorting to multivesicular bodies (Bowers & Stevens, 2005); thus, protein sorting is an important process for growth under ethanol. Smi1p is responsible for coordinating cell cycle progression with cell wall integrity. The ethanol sensitivity of this gene deletion was consistent with a previous study that reported the importance of the regulator of the cell cycle progression under ethanol (Kubota et al., 2004).

Functional categorization of the genes whose deletions resulted in ethanol sensitivity

We classified the genes whose deletions specifically resulted in ethanol sensitivity into functional categories using MIPS (Ruepp et al., 2004). Table 4 lists the functional categories of over-represented genes deleted from strains that were sensitive to 8% ethanol (P<0.01). Functional categories containing a large number of genes related to growth under ethanol stress might have important cellular functions for ethanol stress sensitivity and tolerance.

Table 4.   Representative functional categories of over-represented genes whose deletion strains were sensitive to 8% ethanol
MIPS functional category numberMIPS functional categoryP-valueNo. of genes among selected genes (446)No. of genes among all genes (4138)
01.01.09.06Metabolism of tryptophan1.01E−04816
01.01.09.06.01Biosynthesis of tryptophan2.49E−0457
01.05.04Regulation of C-compound and carbohydrate utilization2.99E−031884
01.20.15.03Biosynthesis of ubiquinone4.58E−0334
02.11Electron transport and membrane-associated energy conservation2.04E−031139
02.13.03Aerobic respiration1.07E−112656
11.04.03.01Splicing2.52E−03929
12.01.01Ribosomal proteins5.70E−1136105
12.07Translational control2.92E−031035
12.10Aminoacyl-tRNA-synthetases2.14E−03614
14.04Protein targeting, sorting, and translocation8.66E−0839151
14.10Assembly of protein complexes2.07E−0831100
16.07Structural protein3.57E−03720
20.01.21RNA transport6.56E−03933
20.09.01Nuclear transport4.17E−041028
20.09.07Vesicular transport (Golgi network, etc.)3.82E−0321106
20.09.07.03ER to Golgi transport3.26E−03930
20.09.10Peroxisomal transport6.64E−03617
20.09.13Vacuolar transport5.71E−0628108
30.01.05.05.01Small GTPase-mediated signal transduction2.55E−031140
42.10.05Nuclear membrane6.54E−0348
42.16Mitochondrion7.99E−1036114
43.01.03.05Budding, cell polarity, and filament formation8.68E−0333202

The deletion strains of the genes classified into the category ‘metabolism of tryptophan’–TRP1, TRP2, TRP3, TRP4, TRP5, ARO1, ARO2, and ARO7– were sensitive to 8% ethanol. We have previously described the ethanol sensitivity of TRP1-5 deletion strains and the ethanol tolerance of strains overexpressing TRP1-3 and TRP5 (Hirasawa et al., 2007). Here, we found that the strains with deleted ARO1, ARO2, and ARO7 genes were ethanol sensitive. Both ARO1 and ARO2 are required for the biosynthesis of chorismate, a precursor of aromatic amino acids, and the deletion of either of them causes tryptophan, tyrosine, and phenylalanine auxotrophy (Lucchini et al., 1978). Figure 3 summarizes the pathway of aromatic amino acid biosynthesis and the sensitivity of these deletion strains to stress. The ethanol sensitivity of the ARO1 and ARO2 deletion strains might be due to the absence of tryptophan biosynthesis. ARO7 encodes chorismate mutase, which converts chorismate to prephenate – a precursor of tyrosine and phenylalanine. The ARO7 mutant was a tyrosine and phenylalanine auxotroph (Ball et al., 1986), indicating that the simultaneous loss of tyrosine and phenylalanine biosynthesis is related to the ethanol sensitivity of the strain with ARO7 deletion.

image

Figure 3.  Aromatic amino acids biosynthesis pathway. This figure is based on ‘superpathway of phenylalanine, tyrosine and tryptophan biosynthesis pathway’ described in SGD; non, E, and N, on the gene represent the sensitivity of its deletion strain under nonstress, 8% ethanol, and 1 M NaCl stresses, respectively.

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We found that the deletion mutants of the genes overrepresented in the functional categories of ‘vesicular transport (Golgi network, etc.)’ and ‘vacuolar transport’ including VPS genes (VPS4, VPS24, VPS25, VPS28, VPS30, VPS35, VPS36, VPS38, VPS54, VPS68, and VPS74) were sensitive to 8% ethanol. The importance of this function with respect to ethanol stress has been described above, and this result was consistent with previous studies (Kubota et al., 2004; van Voorst et al., 2006).

Functional categories of ‘aerobic respiration’ and ‘mitochondrion’ showed a very low P-value. Genes contained in these categories were involved in mitochondrial functions such as ubiquinone (coenzyme Q) biosynthesis (COQ5, COQ9, and COQ10), cytochrome c oxidase (COX7, COX9, COX11, COX12, COX14, COX16, COX18, and COX23), and mitochondrial ribosomal protein (MRP1, MRP49, MRPL6, MRPL7, MRPL13, MRPL20, MRPL22, MRPL25, MRPL27, MRPL32, MRPL33, MRPL37, MRPL38, MRPL40, MRPL49, MRPS5, MRPS8, MRPS17, and MRPS28). Some relationships between mitochondrial function and ethanol tolerance were reported, for example, ethanol sensitivity of the respiratory-deficient strains (Aguilera & Benítez, 1985) and dependence on the mitochondrial genome (Jiménez & Benítez, 1988). Thus, the deletion of these genes caused respiratory deficiency and resulted in the ethanol sensitivity of these deletion strains.

Ethanol sensitivity of strains with a PEX gene deletion

We found that the genes in deletion strains exhibiting sensitivity to 8% ethanol were over-represented in the functional category ‘peroxisomal transport,’ in which strains with deletions of the PEX8, PEX14, PEX15, PEX17, PEX19, and PEX22 genes were scored as ethanol sensitive. Interestingly, the proteins encoded by these genes are involved in peroxisome transport or in the peroxisomal membrane-protein import machinery (Brown & Baker, 2003); further, deletion strains of the genes (PEX1, PEX4, PEX10, and PEX12) that are not included in the ‘peroxisomal transport’ category but whose products are involved in the peroxisome transport machinery were also sensitive to 8% ethanol. The gene names in each category are summarized in Table 5. In contrast, all deletion strains of the PEX genes whose products are involved in peroxisome targeting signaling (PTS2) and regulation of peroxisome size and numbers were not sensitive to 8% ethanol (Table 5).

Table 5.   List of genes associated with peroxisomes
CategoryGene
  1. Underlined genes represent the genes whose deletions resulted in sensitivity to 8% ethanol; the asterisk indicates genes whose deletions resulted in growth defects under nonstress conditions.

Peroxisome transport machineryPEX1, PEX2, PEX4, PEX6*, PEX8, PEX10, PEX12, PEX13, PEX14, PEX15, PEX17, PEX22
Peroxisomal membrane protein import machineryPEX3, PEX19
Peroxisome targeting signaling (PTS2) receptorPEX7, PEX18, PEX21
Regulation of peroxisome size and numbersPEX11, PEX25, PEX27, PEX28, PEX29, PEX30, PEX31, PEX32*
β-Oxidation of fatty acidsCAT2, CTA1, DCI1, ECI1, FOX2, IDP3, MDH3, POT1, POX1, PXA1, PXA2, SPS19
Lysine biosynthesisLYS1, LYS2, LYS4, LYS5, LYS9, LYS12, LYS14

According to the SGD and previous studies (Erdmann et al., 1989; Brocard et al., 1997; Huhse et al., 1998; Koller et al., 1999; Hettema et al., 2000; Rehling et al., 2000; Albertini et al., 2001; Birschmann et al., 2005), the categorized phenotype of all ethanol-sensitive strains with PEX gene deletions is a ‘lack of morphologically recognizable peroxisomes.’ Thus, the disappearance of peroxisomes themselves might cause the ethanol sensitivity of these strains. Furthermore, our results showed that all the strains with deletions of genes encoding peroxisomal matrix enzymes, including those for lysine biosynthesis and the β-oxidation of fatty acids (Breitling et al., 2002), were not sensitive to 8% ethanol (Table 5). The finding that the growth properties of the deletion strains of the enzymes that are functionally associated with peroxisomes and those of PEX deletion strains did not correspond also supports the notion that the absence of peroxisomes results in ethanol sensitivity. This suggested that peroxisomes serve an unknown function(s) associated with growth under ethanol stress.

Deletion strains severely sensitive to ethanol

Deletion strains of LDB19, MEH1, PRO2, and YNL335W exhibited the severest sensitivity to 8% ethanol as shown in Fig. 4. The LDB19 deletion strain exhibited a shortened telomere length and reduced affinity for the alcian blue dye (Askree et al., 2004; Corbacho et al., 2005). However, the relationship between these functions and ethanol stress is not clear. With respect to MEH1, it was reported that the deletion of this gene results in a defect in vacuolar acidification (Gao et al., 2005). It is known that ethanol stress induces intracellular acidification (Rosa & Sá-Correia, 1996) and that the transportation of intracellular H+ to the vacuole by H+ V-ATPase is important for recovery from intracellular acidification (Fujita et al., 2006). Thus, the ethanol sensitivity of the MEH1 deletion strain might be due to a defect in the H+ transportation to the vacuole. PRO2 is involved in proline biosynthesis. It has been reported that strains accumulating proline exhibited ethanol tolerance (Takagi et al., 2005). In our data, the deletion strain of PRO1, which encodes for another component of proline biosynthesis, was also ethanol sensitive. These results suggest that proline is important for ethanol tolerance and that the ethanol sensitivity of the PRO2 deletion strain might be associated with the deficiency in proline biosynthesis. YNL335W encodes only a hypothetical protein; however, our results suggested a function for the product of this gene and its relationship with ethanol tolerance. To further investigate the importance of these genes with respect to ethanol stress tolerance, we constructed the overexpression stains in which each of these genes was constitutively expressed. In this construction, the standard strain BY4742Δhis3 was used as the host strain for overexpression. However, the growth rates of these overexpression strains in the ethanol stress condition were identical to those of the standard strain. The results indicated that although these genes are important for growth under the ethanol stress condition, the amount of their products is not important for improving ethanol stress tolerance.

image

Figure 4.  Growth of ethanol-sensitive strains. BY4742Δhis3 (a), which was used as the standard strain, and the severest ethanol-sensitive strains, LDB19 (b), MEH1 (c), PRO2 (d), and YNL335W (e) deletion strains, were cultivated without (circles) and with (triangles) 8% ethanol addition. Open and filled symbols represent the duplicate data. Arrows indicate the time of ethanol addition.

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Relationship between gene expression and genes of ethanol-sensitive deletion strains

Previously, we have performed genome-wide expression analysis under ethanol stress in yeast (Hirasawa et al., 2007). Here, to investigate the relationship between the change in the expression levels before and after addition of the stress and the effect of gene deletion on the ethanol stress response, we analyzed how the genes screened from the phenotypic data of the deletion strains change their expression levels after the addition of the stress using the data obtained from the genome-wide expression analysis. As shown in Fig. 5, among the genes whose deletion strains showed ethanol sensitivity, the proportion of genes that were upregulated (ratio >2) after the addition of ethanol was significantly low (P<0.05, randomization test) in comparison with all the genes examined (4729 in total). Also, the proportion of genes that did not change their expression levels was significantly high (P<0.01, randomization test). In the up-regulated genes whose deletion strains showed ethanol sensitivity, genes for heat shock protein (HSP26) and trehalose synthesis (TPS1) were included. Genes involved in ergosterol biosynthesis (ERG2, ERG3, ERG5, and ERG6) were included in the downregulated genes. The genes whose expression was not altered included those related to peroxisomal and mitochondrial functions whereas these same genes were identified as required for growth in the presence of ethanol in our screening. Genes that are upregulated under stress conditions are often selected as a target gene for manipulation (i.e. deletion or overexpression) to construct ethanol-tolerant strains. However, our result suggested that the genes whose expression levels were not altered under the ethanol-stressed condition contained a higher proportion of genes important for growth under the ethanol-stressed condition than that of the upregulated genes.

image

Figure 5.  Relationship between genes of ethanol-sensitive strains and gene expression dynamics. White, upregulated genes; light gray, downregulated genes; stripe, genes whose gene expression levels did not change; dark, no gene expression data under ethanol. Each number beside the circle graph represents the proportion of the genes in each category. The number with (*) indicates that the proportions were significantly low (P<0.05), and the number with (**) indicates that the proportions were significantly high (P<0.01) in 446 ethanol-sensitive strains than that in all the 4729 deletion strains.

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Comparison of strains sensitive to ethanol and osmotic stress

We identified the genes that are important for growth under ethanol stress. We then investigated whether these genes are generally important for the stress response by analyzing the growth behavior of deletion strains under osmotic stress, which is usually encountered during bioproduction processes. We aimed to determine which of the genes were specifically important for growth under ethanol stress by subtracting those strains that were sensitive to osmotic stress induced by 1 M NaCl. The relationship between the specific growth rates observed with 8% ethanol and 1 M NaCl is shown in Fig. 6, and the numbers of deletion strains exhibiting sensitivity and tolerance to 8% ethanol and/or 1 M NaCl are described in Table 6. Figure 6 shows that the growth of almost all strains that were cross-sensitive to ethanol and osmotic stress was also defective under the nonstress condition. We excluded the strains showing defective growth under the nonstress condition and found that the stress-sensitive strains were roughly classifiable into groups that were specifically sensitive to either ethanol or osmotic stress. Notably, fewer deletion strains were sensitive to both 8% ethanol and 1 M NaCl (87 strains) than to either 8% ethanol or 1 M NaCl (359 and 242 strains, respectively). These findings indicate that the mechanisms of the response to ethanol and osmotic stress are considerably different.

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Figure 6.  Relationship between specific growth rates of deletion strains under 8% ethanol and 1 M NaCl stress. Red circles, standard strain; blue circles, deletion strains that did not exhibit growth defects under the nonstress condition; light blue circles, deletion strains with growth defects under the nonstress condition. For deletion strains, the average of the specific growth rates of each deletion strains in the two experiments was used. Red and blue lines represent the thresholds for the identification of the strains tolerant or sensitive to both 8% ethanol and 1 M NaCl, respectively.

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Table 6.   Relationship between strains sensitive/tolerant to ethanol and osmotic stress
 1 M NaCl
SensitiveNo changeTolerant
8% Ethanol
 Tolerant020
 No change24234444
 Sensitive873536

After subtracting deletion strains sensitive to osmotic stress from those that were ethanol sensitive, we examined the functional categories to which the resulting group belonged. Table 7 shows that the categories screened were similar to those before subtracting the strains that were sensitive to osmotic stress, except for categories such as ‘regulation of C-compound and carbohydrate utilization’ and ‘small GTPase-mediated signal transduction.’ Here, the functional categories of ‘peptide binding,’‘temperature perception and response,’ and ‘peroxisome’ were identified to be specifically important for growth under ethanol stress. Identification of the ‘temperature perception and response’ was consistent with the report by Piper (1995). Notably, the appearance of the functional category ‘peroxisome’ and persistence of all deletion strains of the genes classified into the ‘peroxisomal transport’ category indicated that peroxisomes are specifically related to growth under ethanol stress.

Table 7.   Representative functional categories of over-represented genes whose deletion strains were sensitive to ethanol but not osmotic stress
MIPS functional category numberMIPS functional categoryP-valueNo. of genes among selected genes (359)No. of genes among all genes (4138)
01.01.09.06.01Biosynthesis of tryptophan1.58E−0347
01.20.15.03Biosynthesis of ubiquinone2.42E−0334
02.11Electron transport and membrane-associated energy conservation3.25E−041139
02.13.03Aerobic respiration6.17E−142656
11.04.03.01Splicing2.50E−03829
12.01.01Ribosomal proteins2.58E−1234105
12.07Translational control5.42E−041035
12.10Aminoacyl-tRNA-synthetases6.73E−04614
14.04Protein targeting, sorting, and translocation9.67E−0630151
14.10Assembly of protein complexes2.18E−0929100
16.02Peptide binding7.51E−0322
16.07Structural protein5.55E−03620
20.01.21RNA transport1.48E−03933
20.09.01Nuclear transport1.96E−03828
20.09.07.03ER to Golgi transport6.94E−04930
20.09.10Peroxisomal transport2.21E−03617
20.09.13Vacuolar transport2.02E−0319108
34.11.09Temperature perception and response6.91E−03515
42.10.05Nuclear membrane2.94E−0348
42.16Mitochondrion1.32E−1236114
42.19Peroxisome3.94E−03831

The over-represented genes for deletion strains that were sensitive to both 8% ethanol and 1 M NaCl were found in the functional categories ‘metabolism of phenylalanine,’‘metabolism of tyrosine,’‘metabolism of tryptophan,’‘isoprenoid biosynthesis,’ and ‘budding, cell polarity, and filament formation’ (Table 8). The ‘metabolism of phenylalanine,’‘metabolism of tyrosine,’ and ‘metabolism of tryptophan’ categories include ARO1, ARO2, and ARO7, whose products are involved in the biosynthesis of the precursors of aromatic amino acids. However, unlike ethanol stress, TRP2-5 deletion strains were not sensitive to osmotic stress (Fig. 3). This finding was consistent with those of González et al. (2007). Thus, the osmotic sensitivity of the ARO1 and ARO2 deletion strains was not due to the absence of tryptophan biosynthesis. The Aro7 protein is involved in tyrosine and phenylalanine biosynthesis; thus, the simultaneous loss of tyrosine and phenylalanine biosynthesis might be associated with the osmotic sensitivity of the ARO1, ARO2, and ARO7 deletion strains. The products of the genes including ERG2, ERG3, and ERG6 categorized into the ‘isoprenoid biosynthesis’ category are involved in ergosterol biosynthesis; further, strains with a deletion of these genes were sensitive to 8% ethanol and 1 M NaCl. Ergosterol is one of the major components of the cellular membrane and is associated with plasma membrane fluidity. This result indicated that ergosterol is important for stress tolerance, which supports previous findings such as a higher ergosterol content in strains that are tolerant to ethanol stress (del Castillo Agudo, 1992) and that the ERG3 and ERG6 deletion strains adapt over time to osmotic stress (Warringer et al., 2003; Fernandez-Ricaud et al., 2005).

Table 8.   Representative functional categories of over-represented genes whose deletion strains were sensitive to both ethanol and osmotic stresses
MIPS functional category numberMIPS functional categoryP-valueNo. of genes in selected genes (87)No. of genes in all genes (4138)
01.01.09.04Metabolism of phenylalanine1.72E−03312
01.01.09.05Metabolism of tyrosine1.31E−03311
01.01.09.06Metabolism of tryptophan2.74E−04416
01.06.01.07Isoprenoid biosynthesis6.82E−03319
10.03.01.01.09G2/M transition of mitotic cell cycle7.90E−03320
11.02.03.04.03Transcriptional repressor9.08E−03321
14.04Protein targeting, sorting, and translocation4.07E−039151
20.09.07.05Intra Golgi transport4.93E−03317
20.09.13Vacuolar transport3.77E−049108
32.01.03Osmotic and salt stress response9.36E−03440
43.01.03.05Budding, cell polarity, and filament formation9.20E−0412202
43.01.03.09Development of asco-, basidio-, or zygospore8.66E−037112

We also found that the functional categories in which osmotic stress-specific sensitive genes were over-represented comprised ‘phosphate utilization,’‘G1/S transition of mitotic cell cycle,’ and ‘stress response’ (Table 9). Under osmotic stress, the HOG1 gene product controls cell cycle progression and is involved in cell cycle arrest at the G1 and G2 phases (Bellíet al., 2001; Escotéet al., 2004; Clotet et al., 2006). We found that deletion strains of the genes classified into the ‘G2/M transition of mitotic cell cycle’ category were sensitive to both ethanol and osmotic stress, whereas deletion strains of the genes classified into ‘G1/S transition of mitotic cell cycle’ were specifically sensitive to osmotic stress, suggesting the importance of cell cycle regulation for growth under osmotic stress.

Table 9.   Representative functional categories of over-represented genes whose deletion strains were sensitive to osmotic but not ethanol stress
MIPS functional category numberMIPS functional categoryP-valueNo. of genes in selected genes (242)No. of genes in all genes (4138)
01.01.06.04.01Biosynthesis of threonine9.83E−0323
01.04.01Phosphate utilization7.16E−0326270
10.03.01.01.03G1/S transition of mitotic cell cycle4.15E−04725
10.03.04.01Centromere/kinetochore complex maturation9.83E−0323
32.01Stress response3.63E−0330310
32.01.01Oxydative stress response5.98E−03848

Of the genes classified into the ‘phosphate utilization’ category, those important for the response to osmotic stress – such as STE20, SSK2, PBS2, and HOG1, which are related to the signal transduction pathway for osmotic stress response [the high-osmolarity glycerol (HOG) pathway; Hohmann, 2002] – were included. The growth of all of these mutants was severely defective under osmotic stress.

Deletion strains specifically tolerant to ethanol or osmotic stress

With respect to the stress-tolerant strains, two deletion strains of CYB5 and YOR139C were specifically ethanol-tolerant, and 10 deletion stains of ALD6, HOC1, PRO1, SCP160, SKY1, TIP41, UBP6, YKL161C, YNR004W, and YNR036C were specifically NaCl-tolerant (Table 10). No deletion strains exhibited a resistance to both ethanol and NaCl.

Table 10.   Genes whose deletion strains were tolerant to ethanol or osmotic stress
NameDescription
Ethanol tolerant
 CYB5Cytochrome b5, involved in the sterol and lipid biosynthesis pathways
 YOR139CDubious open reading frame; partially overlaps SFL1
Osmotic tolerant
 ALD6Cytosolic aldehyde dehydrogenase
 HOC1Alpha-1,6-mannosyltransferase involved in cell wall mannan biosynthesis
 PRO1γ-Glutamyl kinase that catalyzes the first step in proline biosynthesis
 SCP160Essential RNA-binding G protein effector of mating response pathway
 SKY1SR protein kinase involved in mRNA metabolism and cation homeostasis
 TIP41Negatively regulates the TOR signaling pathway
 UBP6Ubiquitin-specific protease
 YKL161CProtein kinase implicated in the Slt2p mitogen-activated (MAP) kinase signaling pathway
 YNR004WPutative protein of unknown function
 YNR036CMitochondrial protein

Among the two genes whose deletions specifically showed ethanol tolerance, YOR139C is a dubious ORF that is located at the complementary strand of SFL1, which is involved in the repression of flocculation-related genes (Robertson & Fink, 1998). CYB5 is involved in sterol and lipid biosynthesis (Lamb et al., 1999); these processes are known to be important for ethanol tolerance (del Castillo Agudo, 1992; You et al., 2003). A more detailed analysis of these genes will provide useful information for understanding the mechanisms of ethanol tolerance.

In the 10 genes whose deletions exhibited osmotic tolerance, the ALD6 and SKY1 deletion strains are known as osmotic-tolerant strains (Forment et al., 2002; Fernandez-Ricaud et al., 2005), suggesting that this list was thought to contain valuable information for osmotic tolerance. PRO1 is involved in proline biosynthesis and its deletion causes proline auxotrophy. The PRO1 deletion strain was reported to be tolerant to NaCl and FK506 (Butcher & Schreiber, 2004). The osmotic tolerance of the proline overproduction strain (Sekine et al., 2007) and the osmotic sensitivity of the PRO2 deletion strain in the present study, which was also required for proline biosynthesis, suggested the importance of proline in the osmotic stress response. The relationship of seven other genes with osmotic tolerance was not identified and further analyses would be required to elucidate the same. Interestingly, six of the 10 osmotolerant strains, i.e. the ALD6, HOC1, PRO1, SCP160, SKY1, and YNR004W deletion strains, exhibited sensitivity to ethanol; however, we could not find any common biological features among these genes. This difference and the absence of overlapping in the tolerant strains between ethanol and osmotic stress suggested different response mechanisms to these stresses in yeast.

Here, we developed a high-resolution culture system and quantified the growth of individual strains with a single gene deletion under nonstress, 8% ethanol, and 1 M NaCl stress conditions. This collection of strains allows the analysis of phenotypic changes caused by a single gene deletion under specific conditions. Quantitative data revealed that genes in the functional categories of ‘peroxisome’ were required for growth under ethanol stress, which was not known previously. The identification of these functional categories in strains cultured on agar plates and measurements of colony sizes produced by deletion strains are difficult because the differences in growth rates between standard and ethanol-sensitive strains are small. However, with our method, we obtained precise growth data under osmotic stress, and screened strains that were specifically sensitive to ethanol stress. Quantitative analysis of the growth of deletion strains will help to generate ethanol-tolerant yeast strains for the bioproduction of useful chemical compounds such as bioethanol. In addition, we identified some deletion strains that tolerated two stress conditions. Further analysis of these strains should reveal the mechanisms of ethanol tolerance.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

This work was supported by Grant-in-Aids for Young Scientists (B) to C.F. (20700270) and T.H. (19780061), respectively, from the Ministry of Education, Culture, Sports, Science and Technology of Japan and a Grant-in-Aid for JSPS (Japan Society for the Promotion of Science) Fellows from JSPS. This work was also supported in part by a grant from the Global COE (Centers of Excellence) Program and a grant of special coordination funds for the promotion of science and technology, Yuragi Project, in Osaka University from the Ministry of Education, Culture, Sports, Science and Technology, Japan.

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  6. Acknowledgements
  7. References
  8. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results and discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Table S1. Specific growth rates of single gene deletion strains. Specific growth rates of all deletion strains at first and second culture under non-stress, 5% ethanol, 8% ethanol and 1M NaCl were listed. In the columns of growth behavior, 0, 1 and 2 represent sensitive, no-change and tolerance respectively for each deletion strain.

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