1Department of Biological Science and Biotechnology, and 2State Key Laboratory of Biomembrane and Membrane Biotechnology, Tsinghua University, Beijing 100084; 3Beijing National Biochip Research & Engineering Center, Jia 2 Qinghua West Road, Beijing 100084, Peoples Republic of China
Received 7 September 2001; returned 18 November 2001; revised 14 December 2001; accepted 4 January 2002.
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Abstract |
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Introduction |
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The yeast Saccharomyces cerevisiae is an ideal eukaryotic organism to study gene expression caused by environmental insults. This organism has a relatively small sequenced genome of c. 6000 genes,6 allowing the construction of a genome-scale DNA microarray. Moreover, the function of c. 68.2% of the S. cerevisiae 6000 open reading frames (ORFs) is known, by genetics, biochemistry or homology,7 which will no doubt aid our understanding of the mechanisms of action of stimuli by chemical agents. The yeast genome-scale DNA microarrays have been employed to monitor global responses to environmental stresses and a variety of chemical agents.8,9 In addition, yeast microarrays are used to study the responses of yeast cells to antifungal agents at the molecular level10 and to predict the mode of action of novel agents with antifungal activity.11
In this study, we monitored the global expression profile changes of 5935 yeast genes caused by treatment with amphotericin B and nystatin. We anticipated a panoramic view of the responses of yeast cells to the two polyene antifungal antibiotics at the molecular level. Efforts have also been undertaken to validate the microarray data in classifying the action of chemical agents by gene expression profiling, since amphotericin B and nystatin have similar physiological and biochemical antifungal mechanisms.
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Materials and methods |
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The S. cerevisiae genomic DNA sequence was downloaded from ftp//ftp.ebi.ac.uk/pub/databases/yeast/orf_seqs/dnaseq. pir in November 1999. Altogether there are 6294 ORFs. The primer selection program PRIMER 0.5 (Whitehead Institute, Boston, MA, USA) was used to design the ORF primers adjacent to the 3' terminus. The main design standard was that all the primers should have very similar annealing temperatures, and the length of PCR products should be between 200 and 1000 base pairs.
ORF amplification and construction of DNA microarrays
Genomic DNA of S. cerevisiae strain S288C was isolated according to Hoffman12 and used as a template for amplification reactions in 96-well PCR plates. The success rate for PCR amplifications with the primer pairs was c. 95% based on the results of agarose gel electrophoresis. PCR products were pre-cipitated with isopropanol and redissolved in 50% dimethyl sulphoxide (DMSO). A commercial arrayer PixSys5500 (Car-tesian Technologies, Irvine, CA, USA) was employed to spot the DNA in DMSO on to poly-L-lysine-treated glass slides. Altogether, 5935 yeast ORFs were arrayed. Additionally, con-trol samples including three different Arabidopsis thaliana DNA fragments (GenBank accession numbers AC004146, AC007661 and U09332), 12 spots of salmon sperm DNA and 12 spots of DMSO were also arrayed. The centre-to-centre distance between two adjacent spots was 225 µm. To verify reproducibility, two identical subgrids (38 x 20 mm for each) of DNA were arrayed on the same glass slide. The detailed procedures for preparing and blocking poly-L-lysine glass slides and denaturing the DNA to be arrayed can be found on the website: http://cmgm.stanford.edu/pbrown/protocols.
Yeast strain and drug exposure
S. cerevisiae strain L1190 (MATa/) was exposed to drug treatment. Amphotericin B and nystatin were obtained from Sigma Chemical Company (St Louis, MO, USA) and dis-solved in DMSO at a concentration of 1 mg/mL. The MICs of the two polyene antibiotics for L1190 were measured according to a previous study.11 A 100 mL culture of YPD (1% yeast extract, 2% peptone and 2% D-glucose) medium was grown to OD600 = 0.8 at 30°C and divided into three flasks, each con-taining 30 mL of culture. Amphotericin B and nystatin were added to cultures to 0.5 x MIC (final concentrations were 2.5 mg/L of both antibiotics). To the control sample was added the same volume of DMSO. After exposure for one doubling time (90 min), yeast cells were collected by centrifugation at 5000 rpm for 5 min at room temperature, flash frozen in liquid nitrogen then transferred to a 85°C refrigerator. Cells were kept at 85°C until they were processed for RNA.
RNA preparation, generation of Cy-labelled cDNA and hybridization
Total RNA was isolated with a hot acidic phenol method.13 Reverse transcription (RT) was performed in a total volume of 40 µL containing 40 µg of total RNA, 1.5 µg of oligo(dT)15 (Promega, Madison, WI, USA), 500 µM each of dATP, dTTP and dGTP, 50 µM dCTP, 25 µM Cy5/Cy3-dCTP (Amersham-Pharmacia, Piscataway, NJ, USA), 40 U RNase inhibitor (Promega) and 400 units M-MLV transcriptase (Gibco, Gaithersburg, MD, USA) in 1x first strand buffer. Three poly(A)+ RNAs, synthesized in vitro from the three arrayed A. thaliana genes, were added to the yeast RNA as internal controls at 0.1, 1 and 10 ng, corresponding to c. 3300 transcripts/cell (assuming the mass of total RNA in a yeast cell is 0.5 pg).14 Briefly, RNA sample and oligo(dT)15 were heated to 70°C for 10 min, quick chilled on ice, and then dNTPs, reaction buffer and enzyme were added and the reaction carried out at 37°C for 2 h. After completion of the reaction, RNA was removed by alkaline hydrolysis. cDNA was precipitated by ethanol and dissolved in 7.5 µL of H2O. Afterwards, 1.5 µL of 20x SSC, 1 µL salmon sperm DNA (10 mg/mL) and 0.2 µL 10% SDS were added to this cDNA solution, boiled for 2 min and cooled to room temperature. To obtain cDNA at a higher concentration, two independent reactions were performed for each RNA sample under identical conditions and the cDNA precipitants redissolved in a total of 20 µL hybridization buffer. After the Cy3- and Cy5-labelled cDNAs were pooled, 40 µL of the mixed cDNA solution was allowed to hybridize to the array at 62°C for 1014 h. When the hybridization was complete, the arrays were washed for 5 min in 200 mL of washing buffer A (0.1% SDS/0.6x SSC) at 50°C, then for 5 min in 200 mL of washing buffer B (0.03x SSC) at room temperature. The glass slides were centrifuged to dryness in 50 mL conical tubes at 1000 rpm for 1 min.
Scanning and data analysis
Arrays were scanned with ScanArray 4000 (Gsi Lumonics, Kanata, OT, USA) and array images were analysed with ImaGene software version 3.0 (BioDiscovery, Los Angeles, CA, USA). To normalize fluorophore-specific variation, spots containing three exogenous DNA fragments of A. thaliana were applied to each quadrant during the arraying process. These elements were used to autobalance the photomultiplier sensitivity setting between the Cy5 and Cy3 channels such that the ratios between the fluorescent intensity of the A. thali-ana DNA spots were close to a value of 1.0. After subtracting the signal intensity on the negative control spots (DMSO spots), the signal was regarded as a real hybridization signal if the spot fluorescent intensity was two-fold higher than the local background. Each experiment was conducted by dye swap.15 If expression ratios were >1.5 or <0.67 with both dye-swap arrays, the corresponding genes were then considered to be expressed differentially, and the average ratio from the change in expression was calculated and treated as the true ratio between the two arrays.
Quantitative RTPCR
Total RNA was extracted as described above and treated with DNase I to eliminate traces of genomic DNA. A fraction of 40 µg total RNA was used to synthesize the first strand of cDNA in 40 µL RT volume. Afterwards, 2 µL of RT reaction products were used as template for PCR amplification in the LightCycler PCR System (Roche Molecular Biochemicals, Mannheim, Germany). The relative RNA transcript abundance was obtained by calculating the ratio of the fluorescent intensity (cross point value) of the treated and that of the control sample by employing the SYBR Green I monitoring method.
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Results and discussion |
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It was found that the stronger the hybridization signals on the arrayed DNA spots, the more reliable were the measured expression alterations. Therefore, we used the same two RT reactions to generate a higher concentration of Cy-labelled cDNA. Of the 5935 yeast genes on the array, 1455 (24.5%) were responsive to amphotericin B treatment, of which 1250 were reduced >1.5-fold, and 205 were increased >1.5-fold. After nystatin treatment, 684 genes were reduced >1.5-fold and 334 genes were increased >1.5-fold. Comparison of the genes responsive to amphoteri-cin B and nystatin showed that of the 1018 (17.2%) nystatin-responsive genes, 771 (75.7%) were also detected in the amphotericin B-treated sample with the same tendency to expression variation despite quantitative differences in the level of change. These should probably not be ascribed to differences in effect of the two antibiotics on yeast cells, but to variation in the hybridization kinetics under different coverslips. It is often observed that even if samples of the same cDNA solution are hybridized to different arrays containing the same DNA spots, there can be a slightly different hybridization signal intensity, which can result in some genes, especially those with low transcript levels, being detected differently on each array. Even so, in our large data pool, there were no examples of a gene that was induced by amphotericin B being reduced by nystatin or vice versa. These results indicate that amphotericin B and nystatin induced highly similar expression profiles in yeast cells, which was consistent with their known similar pharmacological function. All data are available on our website (http://www.capitalbiochip.com/eexp.htm).
Analysis of the amphotericin B-responsive genes
Because the expression profile changes in each gene were in the same directions in cells exposed to amphotericin B and nystatin, we focused our attention on the amphotericin B-responsive genes. These genes are listed in Tables 1 and 2.
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In our experiments, several genes involved in the ergosterol biosynthesis pathway were expressed at a decreased level [ERG4 (1.8-fold), ERG6 (1.8-fold), ERG9 (2.5-fold), ERG11 (2.1-fold) and ERG24 (2.1-fold)]. Concerning genes involved in lipid metabolism, it is noteworthy that some were down-regulated, such as OLE1 and its modulator FAA4, whereas others were up-regulated. INO1, which encodes inositol-1-phosphate synthase, catalysing the formation of inositol-1-phosphate from glucose-6-phosphate, was induced 6.4-fold. It is known that the INO1 gene is the most highly regulated gene in phospholipid synthesis.27 In addition, GIT1, which encodes a putative inositol transporter, and CIT2, which is considered to possess a function similar to GIT1,28 were both up-regulated. These changes in lipid metabolism might suggest a reconstruction of the cell membrane in response to the membrane perturbation caused by amphotericin B. Besides the cell membrane change in response to amphotericin B treatment, three genes involved in cell wall biogenesis, MET5, SPS100 and YMR251W, were induced, revealing that the cell wall may also interfere with the effect of polyene antibiotics, in agreement with previous observations.29,30
In the yeast S. cerevisiae, two networks of genes involved in multidrug resistance (MDR) have been identified. The first one is regulated by Yap1p31 and Cad1p.32 Additionally, an ATP-binding cassette (ABC) transporter, Ycf1p, is required for cadmium resistance mediated by Yap1p.3336 Our results revealed that the expression levels of CAD1 and YCF1 did not change, and YAP1 was repressed by a factor of 2.0. The second network, called pleiotropic drug resistance (PDR),37 is regulated by the transcription factors Pdr1p and Pdr3p. We could not detect the signals of PDR1 and PDR3, perhaps because their transcriptional levels were too low. However, three ABC transporter genes, SNQ2, PDR5 and YOR1, together with PDR15, a member of the PDR network family, were found to have raised their expression levels by factors of 2.1, 2.5, 2.9 and 4.1, respectively. It has been reported that the double deletion of both PDR1 and PDR3 genes results in drug hypersensitivity and strongly reduced expression of SNQ2, PDR5 and YOR1.33,34 Taking all the above information together, it was postulated that amphotericin B possibly triggers the PDR network in yeast cells. In addition to three ABC transporter genes, SNQ2, PDR5 and YOR1, two other MDR transporter-encoding genes, ATR1 and SGE1, which are energerized by proton motive force,38 also increased their expression levels.
We note that two genes, RGT1 and YHR115C, were completely repressed by amphotericin B. The function of YHR115C is as yet unknown; RGT1 functions primarily in regulation of glucose transport. In S. cerevisiae, four HXT genes (HXT14) encode hexose transporters, and Rgt1p is proposed to be a repressor of HXT gene expression.39 How-ever, it was not anticipated that HXT4 would also be repressed by a factor of 3.3, accompanied by complete repression of RGT1, and there were no alterations in the expression levels of HXT1, HXT2 and HXT3. Possibly there are more complicated regulation mechanisms between the RGT1 and HXT genes.
Quantitative RTPCR
To compensate for the sensitivity limitation of northern blots, an alternative method employing a quantitative RTPCR assay based on LightCycler technology was developed.4042 The LightCycler is able to quantify particular dsDNA PCR products by means of SYBR Green I, which fluoresces only when bound to dsDNA. The relative amount of transcript in each cDNA sample is quantified by direct comparison of the cross point value between test and control samples employing the LightCycler algorithmic software. We calculated the fold-alteration (FA) by the formula FA = 2(CP1 CP2), where CP1 represents the crossing point of an RNA sample from treated cells, and CP2 represents the crossing point of an RNA sample from untreated cells. Nine genes were selected to compare their changes at the transcription level in the amphotericin B-treated sample and the control by using microarray and LightCycler quantitative RTPCR methods, respectively. The results shown in Figure 2 indicated a good agreement between measures of changed transcripts obtained by the two methods.
Conclusion
In conclusion, the yeast genome-scale microarray is a highly efficient technology platform to study the mechanisms of action of variants of compounds with antifungal activities. In our next study, we will transfer our focus from these known compounds to those from Chinese traditional herbal drugs, which have been used widely in folk medicine to inhibit or kill fungi but whose mechanisms of action have not been characterized.
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Acknowledgements |
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Footnotes |
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