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Role of the Hog1 Stress-Activated Protein Kinase in the Global Transcriptional Response to Stress in the Fungal Pathogen Candida albicans.

Mol Biol Cell 17: 1018-32 (2006).

Brice Enjalbert^1*, Deborah A. Smith^2**, Michael J. Cornell³, Intikhab Alam³,
Susan Nicholls¹ , Alistair J.P. Brown¹ and Janet Quinn²,

1. Aberdeen Fungal Group, School of Medical Sciences, Institute of Medical Sciences, University of Aberdeen, Aberdeen AB25 2ZD, UK.
2. Institute of Cell and Molecular Biosciences, University of Newcastle upon Tyne, Newcastle upon Tyne NE2 4HH, UK.
3. School of Computer Science, University of Manchester, Manchester M13 9PL, UK

* These authors contributed equally to this study.
  Current Address: Department of Molecular and Cellular Pharmacology, 1580 N.W. 10th Avenue, University of Miami, FL 33136, USA.

Corresponding Authors: Dr Janet Quinn
Faculty of Medical Sciences School of Medical Sciences
University of Newcastle upon Tyne
Institute of Medical Sciences
Newcastle upon Tyne NE2 4HH, UK
E: janet.quinn@ncl.ac.uk
T: 44-191-2227434
F: 44-191-2227424

Prof. Alistair J P Brown
Institute of Cell and Molecular Biosciences
Aberdeen Fungal Group
University of Aberdeen
Aberdeen AB25 2ZD, UK
E: Al.Brown@abdn.ac.uk
T: 44-1224-555883
F: 44-1224-555844

The resistance of Candida albicans to many stresses is dependent upon the Stress Activated Protein Kinase (SAPK) Hog1. Hence we have explored the role of Hog1 in the regulation of transcriptional responses to stress. DNA microarrays were used to characterise the global transcriptional responses of HOG1 and hog1 cells to three stress conditions that activate the Hog1 SAPK: osmotic stress, oxidative stress and heavy metal stress. This revealed both stress-specific transcriptional responses, and a core transcriptional response to stress in C. albicans. The core transcriptional response was characterized by a subset of genes that responded in a stereotypical manner to all of the stresses analysed. Inactivation of HOG1 significantly attenuated transcriptional responses to osmotic and heavy metal stresses, but not to oxidative stress, and this was reflected in the role of Hog1 in the regulation of C. albicans core stress genes. Instead, the Cap1 transcription factor plays a key role in the oxidative stress regulation of C. albicans core stress genes. Our data show that the SAPK network in C. albicans has diverged from corresponding networks in model yeasts, and that the C. albicans SAPK pathway functions in parallel with other pathways to regulate the core transcriptional response to stress.

Strains were grown in at 30°C in YPDAU containing 0.02% adenine and 0.008% uridine. Transcript profiling was performed using isogenic C. albicans strains: wild type (JC52: hog1 cells containing HOG1 reintegrated) and hog1 (JC50). The strains were cultured in YPDAU at 30°C, at 180 rpm to OD600 = 0.5. Cells from the same culture were harvested immediately before and 10 min after stress treatment. Three stress conditions were applied to the cells. Oxidative stress: hydrogen peroxide (H2O2) was added to a final concentration of 5 mM. Heavy metal stress: CdSO4 was added to a final concentration of 0.5 mM. Osmotic stress: pre-warmed YPDAU containing 4 M NaCl was added to a final concentration of 0.3 M NaCl. Cells were collected by centrifugation, frozen rapidly in liquid N2, sheared mechanically using a micro-dismembrator (Braun Melsungen, Germany) and RNA prepared by extraction with Trizol ReagentTM (GibcoBRL), as described previously (Hauser et al., 1998). Cy3 and Cy5-labelled cDNAs were prepared from total RNA, and the probes hybridized with (nearly) whole genome microarrays containing 6,000 C. albicans genes (Eurogentec, Seraing, Belgium). Slides were scanned using a ScanArray Lite scanner (PerkinElmer Life Sciences, Beaconsfield, UK) and quantified using QuantArray software (version 2.0). Data normalization and analysis were performed using GeneSpring (Silicon Genetics, Redwood City, CA), and statistical analysis was performed using SAM (Significance Analysis of Microarrays: Tusher et al., 2001). Expression ratios were calculated by comparing stressed cells with their unstressed control. Data from at least four independent biological replicates were used for each analysis, and the SAM False Discovery Rate was set at 10%. C. albicans gene annotations were obtained from CandidaDB (http://genolist.pasteur.fr/CandidaDB: dÕEnfert et al., 2005). Functional categories for C. albicans genes were assigned using gene ontology (GO) resources at SGD (www.yeastgenome.org/GOContents.shtml), and on the basis of the MIPS functional assignments for S. cerevisiae homologues (http://mips.gsf.de/proj/yeast/CYGD/db/index.html), as described previously (Yin et al., 2004). Promoter analysis was performed using GeneSpring.

These data were provided by Brice Enjalbert and Alistair Brown, Aberdeen Fungal Group, University of Aberdeen, UK.

 

Experimental Data

Species	Candida albicans
Strains	wild type (JC52: hog1 cells containing HOG1 reintegrated)
	hog1 (JC50)
Growth Conditions	All strains (all Ura-) were grown in YPD (+Ade, +Uri) at 30¡C to mid-exponential phase (equivalent to OD600 0.5).
RNA extraction	Harvested cells were frozen by dropping them into liquid N2.  RNA was extracted by the Trizol protocol as described in SOPs.
Labelling	Direct labelling with Cy3/Cy5-dUTP as described in SOPs.
Control RNA (cRNA)	Control on each array was from the other half of the culture RNA samples grown in YPD (+Ade, +Uri) at 30¡C to mid-exponential phase without stresses.
Microarray	Glass microarrays with probes for 5907 C. albicans ORFs as described.
Microarray Manufacturer	Eurogentec SA
Hybrisation Method	As described in SOPs.
Imaging & Data Capture	ScanArray Lite (Perkin Elmer).  Software: ScanArray and QuantArray
Normalisation Method	Intensity dependent (Lowess) normalisation by GeneSpring 7.0 (Silicon Genetics)
Quality analysis	In QuantArray, spots containing dust or dye smears that would give artificially high signals were flagged manually;  GeneSpring did not use these data in further analysis.  Genes that were significantly regulated were identified using SAM software (Tusher et al., 2001) with parameters that minimised the number of possible false positives (FDR<10%).

 

Microarray Data

Txt Files	Bidirectional best hits for Ca, Sc and Sp	Supplementary data
Download all text files (34Mo)	Excel Files Zip (1Mo)	Companion Excel file (15Mo)

 

 

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