1 Departamento de Microbiología II, Facultad de Farmacia, Universidad Complutense de Madrid, 28040 Madrid, Spain
2 Unidad de Genómica, Parque Científico de Madrid/UCM, Campus de Moncloa, Facultad de Ciencias Biológicas, Universidad Complutense de Madrid, 28040 Madrid, Spain
Correspondence
Jose M. Rodríguez-Peña
josemanu{at}farm.ucm.es
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ABSTRACT |
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Present address: Departamento de Toxicología y Legislación Sanitaria, Facultad de Medicina, Universidad Complutense de Madrid, 28040 Madrid, Spain.
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INTRODUCTION |
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The yeast cell wall is an essential structure for cell survival. Globally, the cell wall consists of mannosylated proteins and three kinds of polysaccharide chain (for reviews, see Cid et al., 1995; Klis et al., 2002
). This apparently rigid structure maintains a high degree of flexibility for adaptation to different developmental programs, such as budding, mating and sporulation (Cid et al., 1995
; Duran & Nombela, 2004
; Molina et al., 2000
; Smits et al., 1999
). Treatment with cell-wall-perturbing agents, such as Congo red (CR) and Calcofluor white, or with Zymolyase, which degrades the
-1,3 glucan network, leads to a cellular response, in an attempt by the cell to survive, that has been called the compensatory mechanism. This response clearly illustrates the dynamic nature of the cell wall, and it is characterized by an increase of chitin content, an overproduction of many mannoproteins, changes in the association between cell wall polymers, as well as a transient redistribution of
-1,3 glucan synthase (see Popolo et al., 2001
; Smits et al., 2001
, and references therein). Most of these changes are the consequence of a global transcriptional response that we and other groups have recently characterized both in mutants affected in different steps of the cell wall construction process (Lagorce et al., 2003
) and in wild-type yeast cells growing under different transient cell-wall-damage conditions (Agarwal et al., 2003
; Boorsma et al., 2004
; García et al., 2004
).
The regulation of this compensatory response is mainly controlled by the MAP kinase (MAPK) Slt2p through the cell integrity pathway. This pathway is activated in response to several environmental stimuli, including cell-wall-damage conditions (De Groot et al., 2001; De Nobel et al., 2000
; García et al., 2004
; Gustin et al., 1998
; Ketela et al., 1999
). As a consequence of this activation, a transcriptional program is turned on through the Rlm1p and Swi4p transcription factors, leading to a remodelling of the cell wall (Baetz et al., 2001
; García et al., 2004
; Igual et al., 1996
; Jung & Levin, 1999
). Other authors have also suggested that the Sho1p-Kss1p (Lee & Elion, 1999
) and HOG1-MAPkinase pathways (García-Rodriguez et al., 2000
; Kapteyn et al., 2001
; Klis et al., 2002
) could be involved in the control of cell integrity. Recent genomic approaches have revealed that, in addition to the above-mentioned pathways, the calcineurin/Crz1p signalling pathway and the regulatory machinery from the general cellular stress response could also be regulators of the response to cell wall damage (García et al., 2004
; Lagorce et al., 2003
). However, additional work is still necessary to fully evaluate the role of these pathways in the regulation of this response and to characterize in detail the possible cross-talk between them.
In the present work, we report a custom array (the yeast cell wall chip) for the study of transcriptional variations related to yeast cell wall homeostasis that has a significant number of technical advantages. Based on previous information obtained in our laboratory (García et al., 2004), we have been able to validate this tool for the study of the transcriptional profile of wild-type yeast cells subjected to treatment that induces cell wall stress. The use of this array has also enabled us to obtain novel insights regarding the regulation of the transcriptional compensatory response to cell wall damage of yeast cells lacking the Hog1p MAPK by characterizing the transcriptional profile in response to Congo red.
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METHODS |
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PCR conditions were modified according to the particular Tm of the primers used and the length of the amplified region. Biotools DNA polymerase (Biotools) was used for PCR reactions. PCR products were purified before printing with the Multiscreen PCR 96-well Filtration System (Millipore) and inspected for quality and quantity by gel electrophoresis, following gel analysis in a Molecular Imager Proplus FX using the Quantity One software (Bio-Rad). All PCR products were verified by direct sequencing from at least one side after PCR purification on an automated DNA sequencer 3730 (Applied Biosystems).
Microarray design and printing.
Purified PCR products were spotted onto Ultra-GAPS coated slides (Corning), using a 45 % (v/v) DMSO solution as spotting buffer. For this purpose, we used the MicroGrid II arrayer from BioRobotics. Printing was accomplished with an eight-pin head in a 4x2 pin configuration, each probe being printed in duplicate consecutively, yielding a total of 864 available positions, corresponding to 54 source visits per pin. DNA binding to the surface was done by UV cross-linking following the slide manufacturer's instructions. In the microarray layout (see Fig. 1) there were 778 spots corresponding to S. cerevisiae ORFs, 38 spots were only printed with spotting buffer and were required for the evaluation of basal slide background, 32 spots contained the controls for hybridization specificity (E. coli and S. typhimurium DNA), and finally 16 spots (two printed for each pin) contained the housekeeping gene ACT1. Additionally, the complete grid was printed in duplicate within each slide (separated by 23 mm), giving rise to two independent slide surfaces available for hybridization. Quality control of the printing of each slide batch included staining with Syto61 (Molecular Probes) and hybridization with Cy3-labelled random 9-mer oligonucleotides (Qiagen).
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RNA isolation, cDNA synthesis, and microarray hybridization.
All these processes were basically carried out following the protocols described previously by García et al. (2004), with minor modifications. Briefly, cDNA was synthesized from 1520 µg total RNA (isolated using the RNeasy MIDI kit, Qiagen) by reverse transcription using the CyScribe Post-Labelling Kit, incorporating Cy3-dUTP or Cy5-dUTP (Amersham Biosciences) into the cDNA corresponding to each sample to be compared. Both labelled cDNA populations were combined, dried in a vacuum trap, and used as a hybridization probe after resuspension in 15 µl hybridization solution [50 % formamide, 6x SSC, 0·5 % SDS, 5x Denhardt's, 20 µg poly(A) (P-9403, Sigma) and 100 µg salmon sperm (Gibco-BRL) ml1]. This volume was found to be optimum for the hybridization surface of the tailored microarray described above when hybridization was done under 22x22 mm glass microscopy cover slips (Sigma). The amount of cDNA as well as the incorporation of Cy3 and Cy5 dyes into cDNA targets was quantified on an Ultrospec 3300 Pro UV/visible spectrophotometer (Amersham Biosciences) by measuring the absorbance of each sample at 260, 550 and 660 nm, respectively. For each condition tested, comparing the treated and untreated samples, the total RNA from at least two different cultures was analysed, and in addition for each RNA sample, at least two different hybridizations were performed, including fluorochrome swapping in order to minimize transcriptional changes due to technical variability. Therefore, a minimum of four DNA microarrays was analysed for each experimental condition.
Microarray image analysis.
Microarrays were scanned with a GenePix 4000B scanner (Axon Instruments) at a resolution of 5 µm (PMT values 550700, laser power 100 %). GenePix Pro 4.0 analysis software (Axon Instruments) was used to locate spots in the microarray with the appropriate grid and to obtain the two Cy3/Cy5 image TIFF files. All images were further processed using GenePix 4.0 software, according to the manufacturer's instructions.
Data processing and statistical methods.
Data processing was performed following the protocol described by García et al. (2004). Owing to the small number of features in the yeast cell wall chip with respect to traditional genome-wide microarrays, we had to set up the most convenient normalization method to compensate for treatment (condition assayed)-independent ratio variations. This process was accomplished by evaluating the three most widely used normalization methods (for a review, see Quackenbush, 2002
): i) total intensity normalization, where a normalization factor is obtained from the two channels used (this method assumes that only a few transcripts are regulated by the treatment under investigation); ii) the internal reference method, where the normalization factor is calculated using the data corresponding to a gene with no transcriptional change in the conditions tested (this is the case of the actin gene in this work); and iii) intensity-dependent normalization (Lowess method) to account for systematic biases dependent upon spot intensity. Under our experimental conditions, the second method produced the best results in control experiments, and was therefore chosen for application to all datasets. Significance analysis of the results was conducted using Student's t test (GeneSight 4.0, BioDiscovery). Genes with P values of less than 0·05 were considered to be significantly differentially expressed.
The Microarray data described here follow the MIAME recommendations and have been deposited at the NCBI gene expression and hybridization array data repository (GEO, http://www.ncbi.nlm.nih.gov/geo/) with GEO accession numbers GSE2105, GSE2106, GSE2107 and GSE2108.
Quantification of mRNAs using real-time quantitative RT-PCR (Q-RT-PCR).
Real-time Q-RT-PCR assays were performed as described by García et al. (2004) using an ABI 7700 instrument (Applied Biosystems). For quantification, the abundance of each gene was determined relative to the standard transcript of ACT1 and the final data of relative gene expression between the two conditions tested on each microarray were calculated following the 2
Ct method, as described in Livak & Schmittgen (2001)
. The following forward and reverse primers, respectively, were used: ACT1, 5'-ATCACCGCTTTGGCTCCAT-3' and 5'-CCAATCCAGACGGAGTACTTTCTT-3'; YFL014W, 5'-GTCCACGACTCTGCCGAAA-3' and 5'-GCCAAAGATTCACCTTGACCTT-3'; YLR414C, 5'-TTGGTGCCTTTTTTTCATTTTTC-3' and 5'-GCCCAAACACGAACCTATACTGA-3'; YKR061W, 5'-TCGATTGCTGCCTCACTTCTT-3' and 5'-CAGGTAGTATGCAGATGGACACG-3'.
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RESULTS AND DISCUSSION |
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Evaluation of the double hybridization procedure and validation of the yeast cell wall chip
One of the most important prerequisites in microarray technology is to achieve systems with acceptable reproducibility. For the evaluation of this aspect with the yeast cell wall chip, several control steps were established. First, self to self or yellow experiments were carried out, in which the same RNA sample (from a wild-type yeast strain) was labelled independently with the two fluorochromes (Cy3 and Cy5). As shown in Fig. 2, none of the features present in the array showed significant variations higher than twofold, indicating a good data correlation. Second, we investigated the level of intra-array variability within each complete array (grid). For this and further validation assays, we chose the treatment of yeast cells with the dye Congo red for 4 h as the reference experimental condition. The mechanism of action of this drug is not known, although its interference with proper cell wall assembly is well documented (Kopecka & Gabriel, 1992
). The effect on gene expression brought about by this treatment in wild-type yeast cells has recently been characterized in great detail by our group using microarrays in a genome-wide format (García et al., 2004
). The analysis of the ratios of duplicated spots within the yeast cell wall chip revealed a low degree of data dispersion in terms of deviation from the normal distribution of the data population. This can be deduced from the narrow boxes obtained when the comparisons are represented using box-and-whiskers plots (Fig. 3
). From a quantitative point of view, only about 5 % of the duplicates, on average, differed in ratio by more than two standard deviations (SD) from the mean of the normal distribution.
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Characterization of the transcriptional response to cell wall damage in a hog1 mutant strain
The cell integrity pathway, regulated by the MAPK Slt2p, has been shown to be the main pathway involved in the regulation of yeast cell wall construction (Firon et al., 2004; García et al., 2004
; Jung & Levin, 1999
; Smits et al., 2001
). In agreement, we have previously found that most of the transcriptional response to CR is dependent upon the MAPK Slt2p and the Rlm1p transcription factor activated by this MAPK (García et al., 2004
). However, in silico analysis of the regulatory sequences of the genes involved in the response to the two main groups of cell-wall-stress conditions, transient (García et al., 2004
) or constitutive (Lagorce et al., 2003
), highlighted the possible involvement in this regulation of several other signalling pathways, such as the calcineurin/Crz1p signalling pathway and the regulatory machinery from the general cellular stress response. The involvement of the Hog1p MAPK in the modulation of gene expression in the presence of osmotic stress has largely been characterized (O'Rourke & Herskowitz, 2004
). However, neither the role in gene expression of this MAPK in response to cell wall damage nor the genes that can potentially be influenced by this pathway has been reported. Bearing this in mind, together with the fact that several other reports had also suggested the relationship between HOG1 (the MAP kinase of the high-osmolarity glycerol pathway) and cell integrity (García-Rodriguez et al., 2000
; Kapteyn et al., 2001
; Klis et al., 2002
), we were prompted to examine the role of the MAPK Hog1p in the regulation of the transcriptional response to CR by using our yeast cell wall chip. The transcriptional pattern of a yeast strain lacking Hog1p grown for 4 h in the presence and absence of CR was analysed. We observed that although the absence of HOG1 does not affect the transcriptional activation of most of the genes, this MAPK is essential for the transcriptional activation of HSP12 (YFL014W) and YLR414C (see Table 2
) in response to CR. These data suggest a new role for the Hog1p MAPK pathway in the control of the response to cell wall damage, at least for the genes mentioned above. In order to validate the expression data obtained by microarray analysis, real-time Q-RT-PCR was performed. For this purpose, both Hog1p-dependent genes were analysed by this alternative method. As shown in Table 2
, we found a very good correlation between both datasets, supporting the validity of the yeast cell wall chip experiments. The lack of Hog1p elicited a complete block in the upregulation of HSP12, while this effect was less dramatic in the case of YLR414C (Table 2
). The evidence that the increased expression of these two genes is also completely dependent upon SLT2 and RLM1 (the cell-wall-integrity pathway transcription factor) (García et al., 2004
) supports the existence of genes controlled by different signal transduction pathways, at least dually, as a consequence of cell wall stress. The 800 bp non-coding upstream sequences of both genes were examined using the RSAT program (van Helden, 2003
) searching for motifs of transcription factors related to different signal transduction pathways, including Crz1p, involved in Ca2+/calcineurin-regulated gene expression (Yoshimoto et al., 2002
), the general stress-related factor Msn2p/Msn4p (Martinez-Pastor et al., 1996
), the transcription factor for the pheromone response pathway Ste12p (also required for filamentous growth) and its inhibitor Dig1p (Schwartz & Madhani, 2004
), the activator of pseudohyphal formation Tec1p (Schwartz & Madhani, 2004
), Rlm1p (Dodou & Treisman, 1997
), Hsf1p, which is related to heat stress (Sorger, 1991
), and the HOG pathway transcription factor Sko1p (Proft & Struhl, 2002
) (Table 3
). The presence of this large number of putative regulatory sequences supports the hypothesis of a complex and coordinated regulation of these genes under different situations. Moreover, the dual dependence of YLR414C and YFL014W expression in response to CR on Slt2p and Hog1p could be explained by the presence within the regulatory region of these genes of Rlm1p and Sko1p or STRE binding sites, respectively, and therefore suggests the simultaneous involvement of different transduction pathways (the cell integrity and high osmolarity pathways in this case) in the regulation of the transcriptional response to this specific stress condition. How this control is governed and organized in relation to cell wall homeostasis remains unknown, but a similar situation of dual control has recently been described for the HXT1 gene, a low-affinity glucose transporter, whose expression requires both the glucose-signalling and HOG pathways (Tomas-Cobos et al., 2004
). On the other hand, the transcriptional regulation of FKS2 (encoding the alternative 1,3-
-glucan synthase subunit) is dependent upon both Rlm1p and Crz1p (Jung & Levin, 1999
; Lagorce et al., 2003
). Additional work will be necessary to decipher the putative participation of other signalling pathways on the expression pattern elicited by cell wall damage. In this context, the yeast cell wall chip could be a very useful tool to achieve this goal.
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ACKNOWLEDGEMENTS |
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Received 23 February 2005;
revised 19 April 2005;
accepted 19 April 2005.
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