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Eukaryotic Cell, October 2004, p. 1249-1260, Vol. 3, No. 5
1535-9778/04/$08.00+0 DOI: 10.1128/EC.3.5.1249-1260.2004
Copyright © 2004, American Society for Microbiology. All Rights Reserved.
Departments of Molecular Genetics and Microbiology,1 Medicine,2 Pharmacology and Cancer Biology,3 Howard Hughes Medical Institute, Duke University Medical Center, Durham, North Carolina4
Received 5 May 2004/ Accepted 30 June 2004
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mutants
were extremely sensitive to the ergosterol synthesis inhibitor
fluconazole, indicating a coordination of the synthesis of membrane
component precursors. Unexpectedly, genes involved in amino acid and
pyrimidine biosynthesis were repressed at 37°C, but components
of these pathways were found to be required for high-temperature
growth. Our findings demonstrate the utility of even partial-genome
microarrays for delineating regulatory cascades that contribute to
microbial
pathogenesis. |
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C. neoformans is a basidomycete that is the most common cause of fungal meningitis. C. neoformans infects both immunocompetent and immunocompromised hosts, but disease is generally expressed when the host has impaired immunity. Virulence factors for C. neoformans that have been genetically defined include (i) the ability to synthesize the antioxidant pigment melanin, (ii) the production of an antiphagocytic polysaccharide capsule, (iii) urease and phospholipase production, and (iv) the ability to survive and proliferate at 37°C (13, 14, 37, 45). Proteins that have been identified in C. neoformans as being essential or important for growth at high temperatures include Ras1, the p21-activated kinase (PAK) kinase Ste20, the phospholipid-binding protein Cts1, the vacuolar ATPase Vph1, the thiol peroxidase Tsa1, the cell integrity mitogen-activated protein (MAP) kinase Mpk1, and the Ca2+/calmodulin-dependent phosphatase calcineurin (3, 21, 22, 34, 43, 45, 57). Deletion or disruption of the genes encoding each of these proteins results in either attenuation or complete loss of virulence in mammalian models of cryptococcosis.
The increasing availability of entire genome sequences has resulted in the proliferation of large-scale techniques for studying gene function. For fungal systems where complete genome sequences are not yet available, these techniques have been adapted to provide valuable information about gene expression and function. A major strength of these approaches is that they can provide information that may be difficult to obtain by traditional techniques of genetic analysis; they can also establish a foundation for further study when complete genome sequences become available. cDNA library subtraction and serial analysis of gene expression (SAGE) have been used to identify C. neoformans genes that are preferentially transcribed under conditions of high-temperature growth and in animal models of infection (2, 46, 49, 50, 52). Furthermore, DNA microarrays were adapted for studying phase-regulated gene expression in H. capsulatum prior to completion of the genome sequence (30).
In
this study, we used a similar approach and constructed a shotgun
genomic-DNA microarray to assess C. neoformans
transcription during growth at the human physiological temperature of
37°C. Implementation of this 6,274-element array resulted in
the identification of 239 genes that displayed differential expression
during growth at 37 and 25°C. One differentially regulated
gene, MGA2, encodes a transcription factor homolog that is
required for normal growth in vitro at a range of growth temperatures.
Microarray experiments were performed to identify candidate target
genes of the MGA2 transcription factor which encode orthologs
of components of the fatty acid biosynthesis machinery.
mga2
mutants are hypersensitive to the ergosterol
synthesis inhibitor fluconazole, suggesting a coordination between the
metabolism of fatty acid membrane components and the metabolism of
sterol membrane components. In addition, we report the unexpected
finding that the transcription of genes in amino acid and pyrimidine
biosynthetic pathways decreases at 37°C, yet mutations in
components of these pathways result in a growth defect at high
temperatures. Our studies highlight the potential of genomic approaches
for revealing molecular principles of microbial
pathogenesis.
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), JF99 (MATa ura5),
PK23 (MATa ura5 [URA5]),
PK28 (MAT
mga2
::nat), and AI34
(MAT
clc1
::nat).The growth medium used was 2% yeast extract-1%
peptone-2% dextrose (YPD). For solid media, 2%
agar was added. Nourseothricin was added to solid media at 100
µg/ml, and fluconazole was added at 10 mg/ml. An allele to delete the MGA2 gene and replace it with the nourseothricin resistance cassette by homologous recombination was generated as previously described (16, 23). The construct was transformed into strain H99 by biolistic transformation, and nourseothricin-resistant transformants were screened for deletion of the MGA2 open reading frame (ORF) by PCR and Southern analysis of genomic DNA. The MGA2 gene was reintroduced by transforming a plasmid containing the entire MGA2 gene plus 1 kb each of 5' and 3' flanking DNAs linked to a cassette that confers resistance to G418 (23). Transformants were selected on G418 and tested for the ability to grow in the presence of 10 µg of fluconazole/ml.
Array construction, sequencing, and annotation. The array consists of two components: cDNA clones from strains JEC21 and H99 amplified by PCR with gene-specific primers (130 elements) and shotgun H99 genomic clones (6,144 elements). The H99 genomic library was constructed as follows: 3 to 5 µg of genomic DNA was sheared with a Hydroshear device (Gene Machines) to generate 1.5- to 3-kb DNA fragments, which were cloned as described previously (39), picked and placed in Luria-Bertani-Hogness medium, and stored at 80°C. For sequencing, clones were grown in 96-well plates containing Terrific broth medium in a Higro orbital shaker (Gene Machines), and DNA was isolated by using a RevPrep robot (Gene Machines). Sequencing reactions were performed by using an MJ Research thermal cycler with standard BigDye chemistry (Applied Biosystems). Samples were analyzed on a PE3700 96-capillary sequencer, and data were analyzed and assembled by using the Pare/Phrased sequence package.
PCRs to amplify genomic library inserts were performed by using 64 96-well plates containing bacterial cultures, each of which harbored an independent library transformant. A total of 2 µl of bacterial stock was used for PCR amplification of inserts with vector-specific primers. PCR products were analyzed on 1% agarose gels, precipitated, washed, and printed on polylysine-coated glass slides at the Duke Center for Genome Technology.
Array annotation was performed by comparing array clone sequences with The Institute for Genomic Research (TIGR) JEC21 genome database by using BLASTx (21 January 2004 version, C. neoformans Genome Project). Array clones were assigned JEC21 locus names only when a single BLAST match with an expect value (E value) of between 1050 and 0 was found. The median E value for all array element sequences compared to JEC21 sequences was 10104; however, a large majority of the highly scoring segment pairs produced an E value of 0. Complete annotations, including E values and accession numbers of orthologs, were completed only for elements of interest based on hybridization data. Gene names were assigned to some array clones based on the names of orthologs from other fungal species.
Culture conditions and RNA preparation.
H99
cultures for the 37°C time course were inoculated into YPD
medium and grown at 25°C for 16 h with shaking. The
cultures were diluted to an optical density at 600 nm
(OD600) of 0.2 and returned to 25°C until the
culture density reached an OD600 of 0.8 (approximately
4 h). A portion of the cultures was harvested by
centrifugation at this time, which was considered the 0-h time point.
Cells were diluted in prewarmed YPD medium to an OD600 of
0.1 and incubated for 12 h. Portions of the cultures were
harvested every 3 h during the time course. For steady-state
experiments, the cultures were inoculated into YPD medium and grown for
16 h at 25 or 37°C, diluted to an OD600 of
0.2 with fresh YPD medium, and incubated at 25 or 37°C until an
OD600 of 0.8 was reached. For the comparison of wild-type
and mga2
mutant cells, cultures from isogenic strains
H99 (wild type) and PK28
(mga2
::nat) were
inoculated into YPD medium, grown for 16 h at 30°C,
diluted to an OD600 of 0.2 with fresh YPD medium, and
incubated at 30°C until an OD600 of 0.8 was reached.
Cells from all experiments were harvested by centrifugation, frozen in
ethanol-dry ice, and lyophilized for RNA preparation. RNA was prepared
by using TRIzol reagent (Invitrogen, Carlsbad, Calif.) according to the
manufacturer's
instructions.
Microarray hybridization.
Fluorescence-labeled cDNA was
generated by incorporating amino-allyl-dUTP during reverse
transcription of 10 µg of total RNA. Cy3 or Cy5 dye (Amersham,
Piscataway, N.J.) was coupled to the amino-allyl group as described
previously (18). For the
37°C time course, equal amounts of samples from all time points
were pooled to generate a reference sample, which was labeled with Cy3.
A sample from each time point was individually labeled with Cy5 and
competitively hybridized against the reference sample. For steady-state
experiments, samples from cells grown at 25°C were labeled with
Cy3 and samples from cells grown at 37°C were labeled with
Cy5. Dyes were switched for the reverse fluor control. For
the comparison of wild-type and mga2
mutant cells,
three hybridizations were performed by using wild-type cDNA labeled
with Cy5 and mga2
cDNA labeled with Cy3. In parallel,
reverse fluor control hybridization was performed for each of these
hybridizations.
Data analysis. Arrays were scanned on a GenePix 4000B scanner (Axon Instruments, Foster City, Calif.) and analyzed by using GenePix Pro (version 4.0), Cluster, TreeView, and CryptoArray, a Microsoft Excel macro for normalizing and formatting data (19). Data were normalized for each array element by dividing the background-corrected median pixel intensity of each spot by the sum of the median intensities of all spots on the array (6). This normalization was performed individually for data generated at each wavelength. Gene expression ratios were determined by dividing the normalized intensity in the red channel (635 nm) by the intensity in the green channel (532 nm) for each element. CryptoArray also parses the data to exclude ribosomal DNA and mitochondrial DNA elements and provides the data in the appropriate format for Cluster. For the time course experiments, ratio measurements for each time point were divided by the corresponding ratio measurements for the 0-h time point to cancel the pooled reference sample.
Northern analysis. Samples of 10 µg of total RNA were separated on 1% agarose gels containing 1.85% formaldehyde and transferred to Nytran SuPerCharge membranes (Schleicher & Schuell, Keene, N.H.). The probes used were generated by PCR amplification of cDNA or genomic DNA with gene-specific primers. For genes from the genomic-DNA portion of the array (MGA2, SLG1, CLC1, and RDS1), ORF-specific probes were designed and used for Northern analysis. For known C. neoformans genes included on the microarray (ILV5, SMG1, FHB1, and AOX1), the same PCR products that were printed on the array were used as probes for Northern analysis. Probe labeling and hybridization were performed as described previously (29).
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Assessing temperature-regulated transcription. We used two approaches to identify genes that display differential expression during growth at 25 and 37°C. First, we shifted C. neoformans cultures from 25 to 37°C and assessed gene expression at multiple time points. Time course experiments were performed twice, and representative results are shown in the cluster analysis in Fig. 1. Second, we compared steady-state gene expression in cultures of cells actively growing in logarithmic phase at exclusively 25 or 37°C. These experiments were performed in triplicate, and a reverse fluor control was used in the second trial. By using both temperature shift and steady-state experiments, we reasoned that genes required for both the initiation and the maintenance of growth at 37°C would be revealed in the microarray data analysis. For each experiment, samples were collected and total RNA was prepared. cDNAs were generated from the total RNA samples and differentially labeled with Cy3 (pooled reference sample for the time course experiment and 25°C samples for the steady-state experiment) or Cy5 (individual time point samples for the time course experiment and 37°C samples for the steady-state experiment). These cDNAs were subjected to competitive hybridization on the genomic-DNA microarray. The data for the time course and steady-state experiments are provided in Table S2 in the supplemental material.
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FIG. 1. Gene
expression profiles in temperature shift and steady-state microarray
experiments. Elements whose expression changed at least threefold in at
least one time point after the shift to 37°C or in the
steady-state experiment were analyzed by hierarchical clustering. Each
lane represents a microarray experiment, and each row represents the
expression of an element on the array. For the temperature shift
experiment, cDNAs from the 0-, 3-, 6-, 9-, and 12-h time points were
labeled with Cy5 (red), and a reference sample consisting of equal
amounts of samples from all time points was labeled with Cy3 (green). A
sample from each time point was competitively hybridized against the
reference sample on the microarray. The time course experiment was
normalized against the 0-h time point as described in Materials and
Methods. In the 37 versus 25°C experiments, the 37°C
samples were labeled with Cy5 and the 25°C samples were labeled
with Cy3. The reverse fluor experiment was carried out with samples
labeled "B," and the dye labeling was reversed. For all
experiments, red indicates increased gene expression and green
indicates decreased gene expression. Missing data are represented in
gray. Genes with more than two data points missing were removed from
the cluster analysis. Clusters of interest have been enlarged and are
discussed in the
text.
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Genes induced at 37°C. Table 1 summarizes the genes that were induced during growth at 37°C compared to 25°C. The induction values reported represent the values at which the greatest difference between the 37°C culture and the 25°C culture was observed in either the time course or the steady-state experiment. Genes with orthologs that have known roles in responding to stress were induced at 37°C, including an ortholog of a WSC domain protein gene (SLG1), a chitin synthase gene, a trehalose synthase gene, a trehalose-associated protein kinase gene (RIM15), and genes involved in promoting resistance to reactive oxygen species (catalases and oxidases). In S. cerevisiae, these and other related genes are induced by heat shock and other types of cellular stress as part of a general stress response (25).
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TABLE 1. Temperature-regulated
genes
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FIG. 2. Northern
analysis of temperature-regulated expression. (A) Total RNA
from 25°C samples and 37°C samples was probed with
gene-specific probes. (B) Total RNA from 0-, 3-, 6-, 9-, and
12-h time points was probed with gene-specific probes. ACT1
was included as a loading control in both
experiments.
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Correlation of gene expression profile and mutant phenotype. One goal of this study was to identify genes important for survival at 37°C based on expression profiles after a shift to 37°C or in a steady-state experiment. We identified a gene, MGA2, encoding a transcription factor homolog, whose expression was markedly induced after the shift from 25 to 37°C. In S. cerevisiae, Mga2 and its paralog, Spt23, are involved in regulating transcription in response to cold shock and hypoxia (32, 44). Both transcription factors activate the expression of OLE1, encoding a fatty acid desaturase, suggesting that cell and/or organelle membranes may require remodeling for responses to growth temperature changes (60).
The
C. neoformans ortholog of MGA2 was deleted
by homologous recombination, and its role in promoting high-temperature
growth was assessed. Compared to the isogenic wild-type strain H99, the
mga2
mutant strain displayed slow growth at 25 and
30°C (Fig.
3A). The mga2
growth defect was more pronounced at 37 and
39°C (Fig. 3),
suggesting that this transcription factor homolog plays a significant
role in promoting high-temperature growth. Because fatty acid
metabolism and sterol biosynthesis are coordinated in S.
cerevisiae (11,
36), we tested whether
the mga2
mutation had an effect on C.
neoformans growth in the presence of the ergosterol
biosynthesis inhibitor fluconazole. The mga2
mutant
strain was hypersensitive to 10 µg of fluconazole/ml, while the
growth of wild-type strain H99 was unaffected (Fig.
4A). In a genetic cross with a wild-type MATa strain, the
phenotypes conferred by the mga2
mutation segregated
in a 1:1 ratio of wild type to mutant, and all mutant phenotypes
cosegregated 100% with the nourseothricin resistance marker
(data not shown). Reintroduction of the MGA2 gene into the
mga2
mutant restored its ability to grow in the
presence of 10 µg of fluconazole/ml and complemented the growth
defects (Fig. 4B and data
not shown). The hypersensitivity of the mga2
mutant
to fluconazole likely was due to defects in sterol metabolism, because
the mga2
mutant was also hypersensitive to
fenpropimorph, another sterol synthesis inhibitor, but not to the
protein synthesis inhibitor cycloheximide (data not shown). These
findings suggest that the mechanisms coordinating fatty acid metabolism
and sterol biosynthesis are conserved in C.
neoformans.
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FIG. 3. Phenotypic
analysis of mutant strains. (A) Fivefold serial dilutions of
cultures of H99 (wild type), PK28 (mga2 ), AI34
(clc1 ), JF99 (ura5), and PK23 (ura5
mutant JF99 with URA5 reintroduced) were inoculated into YPD
medium and grown for 3 days at the indicated temperatures.
(B) Cultures of H99 (wild type) (gray bars) and PK28
(mga2 ) (black bars) were inoculated into YPD medium
to an OD600 of 0.05 and incubated at 25 or 37°C for
24 h. Growth was determined by comparing the OD600
of each experimental culture to that of a control culture of the same
strain grown at 30°C for 24 h. Error bars represent
the standard deviation of the mean from three independent
experiments.
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FIG. 4. Deletion
of MGA2 results in hypersensitivity to the ergosterol
biosynthesis inhibitor fluconazole. (A) Cells from wild-type
(H99) and mga2 mutant (PK28) strains were inoculated
into YPD medium and YPD medium containing 10 µg of
fluconazole/ml and grown at 30°C for 3 days. (B)
Reintroduction of MGA2 into the mga2 mutant
restores growth in the presence of fluconazole. Strain PK28
(mga2 ::nat) was
transformed with a plasmid containing the MGA2 gene and a
cassette that confers resistance to G418. Transformants were selected
on G418 at 30°C. Two independent transformants (RC1 and RC2)
were tested for growth in the presence of 10 µg of
fluconazole/ml.
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The CLC1 gene encodes a voltage-gated chloride channel implicated in melanin biosynthesis and ion homeostasis (31, 61). Based on the microarray results, CLC1 was strongly induced after a shift from 25 to 37°C (Fig. 1). This induction was confirmed by Northern analysis (Fig. 2B). Disruption of the CLC1 gene had no effect on the ability of C. neoformans to grow at 37°C (Fig. 3A).
Identifying putative targets of Mga2.
An
important application of microarray technology is the identification of
novel transcription factors and the definition of their targets. Here
we sought to identify targets of the Mga2 transcription factor homolog.
Microarray analysis of wild-type gene expression compared to
mga2
mutant gene expression was performed (Table
2; see Table S3 in the supplemental material). Notably, the orthologs of
the S. cerevisiae FAS1 and ACC1
genes, encoding the beta subunit of fatty acid synthase and acetyl
coenzyme A decarboxylase, respectively, displayed significantly reduced
expression in the mga2
mutant. Cluster analysis of
three independent wild-type and mga2
mutant
microarray experiments and the corresponding reverse fluor control
experiments revealed similar expression patterns for the C.
neoformans FAS1 and ACC1 genes (Fig.
5A). The reduction in FAS1 and ACC1 expression was
confirmed by Northern analysis (Fig.
5B). These results further
support the hypothesis that Mga2 regulates fatty acid biosynthesis in
C. neoformans.
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TABLE 2. Gene
expression in wild-type versus mga2 mutant strains
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FIG. 5. Gene
expression in wild-type and mga2 mutant strains.
(A) Three independent microarray experiments and the
corresponding reverse fluor control experiments were performed with
cDNAs from wild-type (Cy3-labeled) and mga2
(Cy5-labeled) strains. Elements whose expression changed at least
threefold in at least one experiment were analyzed by hierarchical
clustering. Each lane represents one experiment, and each row
represents gene expression. A cluster of interest containing the
FAS1 and ACC1 genes is enlarged. Green color in lanes
1 to 3 represents decreased gene expression. (B) Northern
analysis of wild-type (wt) and mga2 mutant gene
expression. Three independent samples of total RNA from wild-type (H99)
and mga2 mutant (PK28) strains were probed with
FAS1- and ACC1-specific probes. ACT1 was
included as a loading control. (C) Morphogenesis of wild-type
and mga2 mutant strains. Cultures of wild-type (H99)
and mga2 mutant (PK28) strains were inoculated into
YPD medium and incubated at 37°C for 24 h.
Differential interference contrast images were captured at a
magnification of x1,000 with a Zeiss Axioskop 2 Plus microscope
equipped with an AxioCam MRM digital
camera.
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mutant strain compared to the
wild-type strain were several whose products are implicated in
regulating polarized cell growth. The expression of two homologs of
small GTPase effectors was significantly higher in the
mga2
mutant strain than in the wild-type strain
(Table 2). GTPase modules
play important roles in directing polarized growth in S.
cerevisiae and other fungi
(10,
26,
58). In addition, the
expression of PAK1, encoding a PAK kinase important for
filamentous growth during C. neoformans mating, was
higher in the mga2
mutant strain than in the
wild-type strain (57).
Taken together, these results indicate that cells lacking Mga2 are
defective in the regulation of polarized cell growth. Cultures of
wild-type and mga2
mutant cells were grown in YPD
medium at 37°C for 24 h and examined by microscopy
(Fig. 5C). Approximately
50% of mga2
mutant cells displayed defective
morphology, including multiple buds and misshapen buds (n
= 200). Less than 1% of wild-type cells grown under the
same conditions displayed defects in bud morphology. These findings
support the hypothesis that Mga2 plays a role in the morphogenesis of
C.
neoformans. |
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A goal of this study was to identify genes important for growth at 37°C, a crucial virulence attribute of C. neoformans. Analysis of gene expression changes that occur after a shift from 25 to 37°C and the steady-state comparison of 25°C growth versus 37°C growth revealed important features about how this fungus adapts to alterations in growth environment. Genes that are important for stress responses are induced upon a shift from 25 to 37°C. Among the induced genes are orthologs of trehalose synthase, catalase, superoxide dismutase, and a presumptive sensor of cell wall stress. It is important to note that for those genes that were induced only at later time points after the shift from 25 to 37°C, induction may be the result of long-term adaptation to growth at 37°C or an indirect consequence of increased cell density. An example of this phenomenon is the pattern of expression of the alternative oxidase AOX1, which is initially repressed after a shift to 37°C but then is strongly induced by 12 h after the shift. FHB1, encoding flavohemoglobin, displays a similar pattern of expression as AOX1. Both FHB1 and AOX1 play roles in responding to nitrosative and oxidative stresses, respectively (2, 17). It is unclear why these genes would be initially repressed after exposure to heat stress; however, the regulation of these genes or their products at posttranscriptional levels in response to environmental changes is possible.
Heat shock induced gene expression is a phenomenon observed in both S. cerevisiae and Candida albicans (20, 25). These two fungi differ in that S. cerevisiae undergoes a general stress response, involving an extensive gene expression program that is initiated regardless of the specific stress encountered, whereas C. albicans does not. Our studies suggest that it is possible to test whether a general stress response exists in C. neoformans by using the genomic microarray. One important component of the response to high-temperature growth in both S. cerevisiae and C. albicans is the induction of heat shock proteins that act as molecular chaperones. Our array contains orthologs of the heat shock proteins HSP78 and HSP104, and these genes display an approximately twofold increase in expression in the 3-h time point after the shift from 25°C growth to 37°C growth (data not shown). An ortholog of the SSA family of heat shock chaperones showed no significant change in expression. The failure to detect induction of these heat shock protein genes to similar levels as in S. cerevisiae is likely due to differences in experimental design, in that the first time point taken in our study was 3 h after the temperature shift, rather than 10 to 30 min, as in the S. cerevisiae and C. albicans studies.
Recently, Steen et al. analyzed temperature-regulated transcription in C. neoformans using SAGE (49). In that report, gene expression at 25 and 37°C was studied for both the serotype D strain B3501A and the serotype A strain H99. Although SAGE and microarray hybridization use different technologies to probe gene expression, it is reasonable to expect overlap in the microarray data and the SAGE data. We find similarities in the genes whose expression is higher at 37°C than at 25°C in our transcriptional profiling of H99 and the SAGE report analyzing the serotype D strain B3501A. Most notably, the genes encoding homologs of an aryl alcohol oxidase (SMG1) and a peripheral benzodiazepine receptor were more highly expressed at 37°C in both studies. Among genes that are repressed at 37°C, the ribosomal proteins P0 and S26 were found in our study and the SAGE analysis of both temperature-regulated transcription and gene expression during experimental cryptococcal meningitis, suggesting that alterations in protein synthesis are important for tolerating high-temperature growth and in vivo growth (49, 50).
That
differences exist in our study and the SAGE studies is also not
surprising given differences in experimental design. An advantage of
microarray studies is the ability to analyze changes in gene expression
over a time course, while the SAGE experiments described by Steen et
al. (49) were performed
at a single time point. Additionally, Steen et al. found significant
differences in the patterns of expression for strains B3501A and H99 in
their study. Transcriptional analysis of strain B3501A reveals that
genes involved in lipid metabolism, such as genes encoding
9
fatty acid desaturase and fatty acid synthase, were more highly
expressed at 25°C. We found that a transcription factor homolog
that may target lipid metabolism genes is strongly induced at
37°C (see below). These differences could reflect unique
properties of C. neoformans serotype D strains such
as B3501A relative to the more thermotolerant serotype A strain H99.
However, changes in membrane composition and fluidity are likely to
occur during growth at either low- or high-temperature extremes
(1,
48,
51).
Microarray
analysis identified a gene, MGA2, that shows significantly
higher expression during growth at 37°C and that is also
important for normal growth at high temperatures. However, this
approach does not appear to be generally applicable. In S.
cerevisiae, genes that protect against DNA damage are not
significantly induced in the presence of DNA-damaging agents
(7). Of the previously
identified genes important for C. neoformans
high-temperature growth (CNA1, CNB1, CTS1,
STE20, MPK1, and RAS1), none displayed
significantly higher gene expression during growth at 37°C than
during growth at 25°C. MPK1 encodes a MAP kinase in
the protein kinase C-mediated cell integrity pathway and therefore
might be expected to display an increase in expression upon a
temperature shift; however, no such increase in expression was
observed. Furthermore, CLC1 was induced strongly in the
earliest time points after the shift to 37°C (Fig.
1); however, a
clc1
mutant was not affected in its ability to
tolerate high-temperature growth (Fig.
3A). Strikingly, we
observed a significant reduction in expression of genes involved in
isoleucine or valine biosynthesis and pyrimidine biosynthesis after a
shift to 37°C, yet mutations inactivating each of these
pathways result in a high-temperature growth defect. This is an
unexpected result, and an explanation may be that the
ilv2
and ura5
mutants accumulate a
toxic intermediate at 37°C but not at 25°C or that the
uptake of essential nutrients is significantly altered by the growth
temperature, the presence of the mutations, or both. This expression
pattern may not occur for all amino acid biosynthetic pathways, as
genes encoding homologs of lysine and threonine biosynthetic enzymes
are induced rather than repressed at 37°C (Table
1). These results suggest
caution may be warranted in the use of URA5 as a selectable
marker and in the interpretation of experiments using ura5
mutant strains. Interestingly, we found no evidence of
temperature-sensitive growth defects in serotype D ura5
mutants, whereas serotype A ura5 mutants are clearly
temperature sensitive (A. Idnurm, P. Kraus, and J. Heitman,
unpublished data). Although identification of genes that
display differential expression may not in all cases reveal
physiologically relevant patterns of gene expression, microarray
analysis can be used effectively as a screen to prioritize candidates
for further study. Hence, an essential component of studies with the
C. neoformans genomic microarray is incorporation of
information regarding phenotypic consequences of alterations in gene
expression.
Long-chain fatty acids are used by eukaryotic cells
as an energy source as well as for building blocks of cell and
organelle membrane lipids. S. cerevisiae has served
as an excellent model system for studying fatty acid metabolism, and
considerable information is known about how fatty acids are
synthesized, transported, and degraded
(54). An important
component of the regulation of fatty acid metabolism in yeast cells is
the activation of gene expression, with signals such as glucose and
unsaturated fatty acids acting to induce the expression of a panoply of
target genes. The expression of genes involved in saturated fatty acid
biosynthesis, including ACC1 and FAS1, is coregulated
(12). Our results suggest
that these genes are also coregulated in C.
neoformans, and a transcription factor homolog that may target
these genes was identified. C. neoformans Mga2 is
homologous to two S. cerevisiae transcription
factors, Mga2 and Spt23. These factors activate expression of
OLE1, encoding
9 desaturase, in response to low
oxygen levels and low growth temperatures
(32,
60). Other targets of
these factors in yeast cells, if any, are unknown. Membrane composition
is altered when S. cerevisiae cells are exposed to
temperature extremes, and activation of desaturases is thought to
provide increased membrane fluidity
(48,
51). In C.
neoformans, increased production of long-chain fatty acids may
be necessary for tolerating high-temperature growth and could explain
the increased expression of a factor regulating their production. It is
important to note that expression of the potential targets of Mga2,
FAS1 and ACC1, was not significantly higher at
37°C than at 25°C (Table
1; see Table S2 in the
supplemental material). Mga2 and Spt23 are synthesized as precursors
that are anchored to the endoplasmic reticulum membrane and then
activated by ubiquitin- or proteasome-dependent processing
(28). Hence, an increase
in the expression of the MGA2 and SPT23 genes may not
result in a concomitant increase in activity of the transcription
factors. S. cerevisiae MGA2 expression is
induced by the unfolded protein response, suggesting that additional
pathways may be targeted by this transcription factor
(53). Increased
expression of MGA2 in C. neoformans may be a
consequence of the unfolded protein response or endoplasmic
reticulum-mediated protein degradation, both of which are activated by
heat stress in S. cerevisiae
(25,
53). Nevertheless,
C. neoformans MGA2 plays an important role
in cell growth, particularly at high growth temperatures.
Fatty
acid metabolism is coordinated with sterol synthesis in yeast cells,
and antifungal drugs that inhibit ergosterol biosynthesis may also have
secondary effects on the enzymes that catalyze fatty acid biosynthesis
(11,
35,
36). The C.
neoformans mga2
mutant is hypersensitive to
the ergosterol synthesis inhibitor fluconazole, indicating a conserved
link between fatty acid and sterol metabolism. Membrane remodeling via
fatty acid biosynthesis, saturation-desaturation, and sterol metabolism
is likely to be an important component of the regulatory mechanisms
enabling responses to stress in C. neoformans.
Interestingly, the sterol composition of C.
neoformans can be altered after passage through a mammalian
host (15). Additionally,
lipids and sterols are important components of polarized cell growth in
S. cerevisiae and S. pombe, and our
findings suggest that this relationship is conserved in C.
neoformans (5,
56). The effects of
improper regulation of fatty acid and sterol metabolism in C.
neoformans influence the ability to undergo normal
morphogenesis, which is essential for growth, mating, and haploid
fruiting (4). The wiring
of regulatory pathways that respond to stress, coordinate fatty acid
and sterol synthesis, and control cellular morphogenesis likely differs
between S. cerevisiae and C.
neoformans and may differ among the closely related varieties
of C. neoformans. Detailed examination of these
pathways will provide additional insight into the biology underlying
stress responses and potentially reveal new areas to pursue for
antifungal therapy.
We acknowledge the C. neoformans Genome Project, Stanford Genome Technology Center, funded by the NIAID/NIH under cooperative agreement AI47087, and TIGR, funded by the NIAID/NIH under cooperative agreement U01 AI48594, for providing gene sequence and annotation information prior to publication. These studies were supported in part by R01 grants AI39115, AI42159, and AI50438 from NIAID to J.H., grant A128388 to J.R.P., and program project grant P01-AI44975 from NIAID to the Duke University Mycology Research Unit. Gary M. Cox is a Burroughs Wellcome New Investigator in Molecular Pathogenic Mycology. Joseph Heitman is a Burroughs Wellcome Scholar in Molecular Pathogenic Mycology and an Associate Investigator of the Howard Hughes Medical Institute.
Supplemental material for this article may be found at http://ec.asm.org/. ![]()
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