1 Department of Developmental Biology, Stanford University, Stanford, CA 94305,
USA
2 Department of Genetics, Stanford University, Stanford, CA 94305, USA
* Author for correspondence (e-mail: kim{at}cmgm.stanford.edu)
Accepted 30 December 2002
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SUMMARY |
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Key words: Dauer, Microarray, Timecourse, C. elegans
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INTRODUCTION |
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Genetic and molecular analyses (Riddle
and Albert, 1997) have revealed that dauer-inducing pheromone is
detected by sensory neurons that subsequently regulate larval development
through the TGFß (Ren et al.,
1996
) and cGMP (Birnby et al.,
2000
) signaling pathways. An insulin-like
(Kimura et al., 1997
)
signaling pathway acts in parallel to control dauer entry in a
pheromone-independent mechanism (Gottlieb
and Ruvkun, 1994
). Neuroendocrine cells probably integrate the
manifold inputs from the insulin-like and TGFß signaling pathways and
then distribute the decision to become dauer to target tissues, in a
daf-12 nuclear hormone receptor-dependent manner
(Antebi et al., 2000
).
Dauer recovery is initiated once environmental conditions become favorable,
particularly a high food to pheromone ratio and low temperature
(Golden and Riddle, 1984).
Upon transfer to favorable conditions, the first visible change is a change in
surface lipophilicity (30 minutes), and commitment to dauer recovery occurs
after approximately 50-60 minutes (Golden
and Riddle, 1984
; Proudfoot et
al., 1993
). Pharyngeal pumping, movement and increased body volume
occur within 3 hours at 25°C (Cassada
and Russell, 1975
). There is a shift in internal pH from about pH
7.3 to about pH 6.3 prior to feeding
(Wadsworth and Riddle, 1988
).
The recovering dauer molts into a post-dauer L4 at
10 hours at 25°C
(Cassada and Russell, 1975
).
There are distinct sets of temporally regulated genes expressed upon exit from
the dauer stage (Dalley and Golomb,
1992
); expression of the Hsp70 and polyubiquitin genes peaks 75
minutes before the pharynx begins to pump and diminishes within 4 hours. SAGE
analysis of dauer animals identified 358 genes that are dauer specific
(Jones et al., 2001
).
Dauer larvae have been described as `non-aging', as post-dauer lifespan is
not affected by the duration that an animal spends in the dauer state
(Klass and Hirsh, 1976).
Dauers can survive five times the normal lifespan (at least 70 days). Dauer
longevity might be mediated in part by increased expression of stress
resistance genes, decreased metabolic rates and by the insulin-like signaling
pathway (Dorman et al., 1995
;
Kenyon et al., 1993
;
Tissenbaum and Ruvkun,
1998
).
C. elegans dauer larvae have been considered analogous to the
infectious larvae of parasitic nematodes because of morphological, behavioral
and physiological similarities (Bird et
al., 1999; Blaxter and Bird,
1997
; Burglin et al.,
1998
). Additionally, muscarinic-receptor agonists induce recovery
from the dauer stage in both C. elegans and the parasitic nematode,
Ancylostoma caninum, indicating conservation at the neuronal level
for these two species (Tissenbaum et al.,
2000
). Although the dauer stage is facultative in C.
elegans, it is often obligatory in other species. As parasitic nematodes
can infect humans and agricultural crops, a fundamental understanding of the
mechanisms that underlie the dauer state in C. elegans might
illuminate methods for control of nematodes that are pests
(Aboobaker and Blaxter, 2000
;
Blaxter and Bird, 1997
).
Analysis of dauer recovery in C. elegans could help define a
conserved developmental transition for all nematodes.
In this paper, we have profiled gene expression patterns of the C.
elegans dauer and associated dauer recovery process by using high-density
DNA microarrays (Schena et al.,
1995). Microarray analysis permits parallel and unbiased
identification of genes that might have multiple functions, genetic redundancy
or subtle phenotypes. We hypothesized that some of the transcriptional changes
might simply be a response to the introduction of food rather than to
development events per se, so we compared gene expression changes during dauer
exit to those following exit from starvation. These experiments define a
molecular profile for the dauer state involving 1984 dauer-regulated and 446
feeding-regulated genes.
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MATERIALS AND METHODS |
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Dauer growth and purification
Dauers were isolated as previously described with minor modifications
(Epstein and Shakes, 1995).
Wild-type (N2) C. elegans were grown on egg white plates for 8-12
days at room temperature (
22.5°C) until dauers had become plentiful.
Worms were first isolated by washing with 0.1 M NaCl and sucrose floatation.
Next, dauers were purified by treating the worms with 1% SDS for 1 hour,
sucrose floatation and pelleting through 15% Ficoll. Purification was slightly
variable, and in the worst case, estimated to be about 1:1 dauer to carcass by
mass and 1000:1 dauers to non-dauers. Approximately 0.5 to 1 ml of this dauer
sample was kept for the 0 hour time point, and a similar amount of worms were
inoculated onto E. coli (OP50) seeded 15 cm plates for each time
point. Concentrated E. coli paste derived from a fermentor was added
to the plates at 0, 3 and 8 hours to prevent starvation. Each timecourse was
repeated four times with the exception of the 4 and 7 hour time points, which
only have three repetitions each.
During the course of our data analysis, it became clear that the carcasses contributed RNA. Carcass-derived RNA appeared dauer enriched as this RNA gradually degraded during the dauer exit timecourse. To filter out genes that change due simply to RNA degradation in carcasses, we analyzed four populations of pure dauers. We purified dauers through a nylon mesh with 15 µm pores for 20 minutes. In the worst case, the ratio of dauer to carcass was estimated to be about 33:1 and dauer to non-dauer worms was 1000:1. RNA was purified from the pure dauer populations before (0 hour) and after (12 hour) feeding with E. coli.
Isolation of L1 larvae
L1 larvae were isolated as previously described with minor modifications
(Epstein and Shakes, 1995).
Briefly, embryos were prepared by hypochlorite treatment, and were hatched in
0.1M NaCl overnight. L1 larvae were purified by sucrose floatation to remove
dead carcasses, and allowed to recover in 0.1 M NaCl overnight. The starved L1
larvae were then plated onto 15 cm plates seeded with OP50. More E.
coli was added at 3 and 8 hours to prevent starvation.
RNA preparation and microarray hybridization
The reference RNA used for all experiments is from a mixed staged
population of N2 worms grown at room temperature (22.5°C). Worms were
harvested by washing the plates twice with 0.1 M NaCl at room temperature and
then suspending in six volumes of Trizol. Total RNA and polyA(+) RNA were
isolated as previously described (Reinke
et al., 2000
). Reference and experimental cDNA probes were labeled
with Cy3 and Cy5, respectively, from 5-10 µg of polyA(+) RNA as previous
described (DeRisi et al.,
1997
). Reference and experimental probes were purified with a
Qiagen PCR purification kit and 28 µl subsequently hybridized (labeled
probe, 8.3 mM Tris, 2xSSC, 0.17% SDS and 0.67 µg yeast tRNA) to near
full-genome C. elegans DNA microarrays
(Jiang et al., 2001
).
Data analysis
Scanning was carried out with an Axon 3000 scanner. Data was acquired and
quantitated with GenePix software. The raw data were uploaded into the
Stanford Microarray Database. Normalized data [log2
(experiment/reference)] were downloaded using the following filter criteria:
flag=0, failed=0, spot size >13 pixels, and red or green intensity
>1.5-fold of the background intensity.
To identify genes that change in expression during the dauer exit timecourse, a standard one-way ANOVA (P<0.001) was applied to each gene. There were 2650 genes that passed these criteria, including genes that were derived from contamination from carcasses. Contaminating genes would appear downregulated in the dauer exit timecourse but not downregulated when comparing the 0 hour time point with the 12 hour time point using pure dauers. Contaminating genes would also be more enriched in the samples containing carcasses in comparison to the samples with pure dauers (at 0 hours). Specifically, we looked at the downregulated genes and removed genes whose expression was greater in the samples containing carcasses than in the pure dauer sample at 0 hours (one-tailed Students t-test, P<0.05) and that did not show significant downregulation in dauer exit using pure dauers (0 hours versus 12 hours, one-tailed Student's t-test, P>0.001). In this fashion, we removed 220 genes that were likely to be due to contamination from carcasses. The remaining 2430 genes are differentially regulated during the dauer exit timecourse and are reported in the Results.
For these 2430 genes, we employed a two-way mixed-model ANOVA as
implemented by SAS to identify 1984 genes with different kinetics between the
dauer exit and L1 starvation timecourses (P<0.05)
(Romagnolo et al., 2002). We
used a self-organizing map to cluster the 1984 genes of the dauer-specific
data set into 45 nodes using 15 million iterations with Cluster software
(Eisen et al., 1998
). We used
hierarchical clustering followed by visual inspection to subdivide the 45
nodes into the five groups described in the Results. For all other analyses,
we used hierarchical clustering to organize individual genes. To compare
whether gene classes were over-represented with respect to subsets of the
data, we used the hypergeometric probability (J. Lund, data not shown).
Treeview software was used to facilitate visualization of the microarray
expression data (Eisen et al.,
1998
). When reporting the magnitude and confidence of
dauer-enrichment in Figs 4,
5, we used the 12 horr/0 hour
time point ratio and one-tailed Student's t-test P values
derived from comparing the pure dauer 0 hour time point with the pure dauer 12
hour time point. Most gene annotations are from Proteome but some are manually
annotated (e.g. different isoforms of daf-16). Gene lists are from
Proteome, Kim et al. (Kim et al.,
2001
) or manually compiled.
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RESULTS |
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We wanted to generate a high temporal resolution of the dauer exit process,
so dauer animals were harvested at approximately 1 hour intervals over 12
hours after feeding. In order to engage statistical analysis, each timecourse
was repeated four times. The L1 starvation timecourse involved a similar
timecourse after feeding of starved L1 worms. From each experimental sample,
we purified polyA(+) RNA, synthesized Cy3-labeled cDNA and compared it with
Cy5-labeled reference cDNA synthesized from mixed-staged wild-type
hermaphrodite polyA(+) RNA. We hybridized both probes to DNA microarrays
contained 17,088 genes that correspond to 88% of the known predicted genes
(Jiang et al., 2001) (M.
Kiraly, personal communication). For each hybridization, we calculated the
log2 of the expression level of the experimental sample relative to
the expression level of the reference, and then averaged the results for the
three or four replicates of each time point. Because all of the samples were
compared with the same reference RNA, we could compare the expression levels
of one time point to any other in either timecourse. We plotted how each gene
behaved in the dauer recovery and L1 starvation timecourses relative to the
starting time point (0 hours). The complete data for the dauer recovery and L1
starvation timecourses as well as an application to view expression profiles
for individual genes can be viewed at
http://cmgm.stanford.edu/~kimlab/dauer/
Statistical analysis
To identify genes that were significantly induced or repressed during the
dauer exit timecourse, we first used one-way ANOVA analysis to identify 2430
genes that change expression in the dauer exit timecourse
(P<0.001; Materials and Methods) (see supplemental Table S3 at
http://dev.biologists.org/supplemental/
and at
http://cmgm.stanford.edu/~kimlab/dauer/ExtraData.htm).
The large number of genes identified is not unexpected as dauer larvae are
highly differentiated and proceed through a dramatic change during exit. Some
of the 2430 genes are related to the introduction of food while others might
be specific to dauer exit. We distinguished between these two categories by
comparing the expression profile of the dauer exit and L1 starvation
timecourses using two-way mixed-model ANOVA (P<0.05). This
analysis identified 1984 genes that were considered to be differentially
expressed between the two timecourses (see supplemental Table S4 at
http://dev.biologists.org/supplemental/
and at
http://cmgm.stanford.edu/~kimlab/dauer/ExtraData.htm).
Feeding response
Enriched gene groups
The feeding response is defined by a set of 446 genes that change in the
dauer exit timecourse and whose expression kinetics in the L1 starvation
timecourse are not significantly different from the dauer exit timecourse
based on two-way mixed-model ANOVA (P>0.05,
Fig. 1). We compared the
feeding response genes to groups of previously defined functional classes to
determine which classes were statistically over-represented. We calculated a
representation factor, which is the fold-enrichment of a particular class of
genes over the number expected as a result of random chance given the number
of genes in each group and the genome size. A gene class that is highly
enriched suggests that its biological function plays an important role during
recovery from starvation.
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Enriched gene expression mountains
Kim et al. have organized genes into 44 groups based on correlated
expression across 553 diverse experiments
(Kim et al., 2001). The
algorithm used to generate the gene groups produced a 3D output for visual
representation (a gene expression topomap) in which the gene groups appear as
mountains of co-expressed genes (Kim et
al., 2001
). Six gene-expression mountains are significantly
over-represented in the feeding response
(Table 1). Five (mounts 2, 18,
20, 40 and 41) are enriched for genes involved in protein expression or
synthesis (Table 1) (Kim et al., 2001
). Three of
these (mounts 2, 18 and 20) are also enriched for biosynthesis genes. These
results provide further evidence that genes involved in protein expression and
biosynthesis are involved in the feeding response. The sixth mountain (mount
5) is not enriched for any previously defined gene classes.
The gene expression mountains can also be used to partition the list of feeding response genes into smaller clusters; each cluster contains genes that are co-expressed not only during feeding but in a diverse set of microarray experiments used to generate the expression topomap. Genes within a mountain exhibit tight co-regulation, and tight clustering of genes on the topomap is evidence that these genes may function together. The list of feeding response genes includes those whose function are known (e.g. because they encode proteins similar to proteins of known function) and also many genes with unknown function. We can use the expression topomap to infer the function of these unknown genes based on co-expression with genes of known function. For example, the feeding response genes whose functions are currently unknown and that are in mounts 2, 18, 20, 40 and 41 are likely involved in biosynthesis or protein expression. Similarly, genes with unknown function in other mountains could match the ascribed function of that mountain.
As genes within a mountain exhibit tight co-regulation across many experiments, the gene expression mountains can be used to find additional genes that may be involved in the feeding response. For example, we plotted all of the genes in mounts 40 and 41 in the dauer and L1 starvation timecourses and found that almost all are upregulated in both timecourses (Fig. 2). These two mountains include not only the five genes that were found by these microarray experiments but also an additional ten genes that appear to be upregulated in both timecourses. Hence, these ten genes are likely to be feeding response genes; they are co-expressed in these gene expression mountains but were probably missed because they did not meet the stringent statistical criteria used by the ANOVA analysis. These results show that feeding response is another characteristic that underlies the expression profiles of the genes in mounts 40 and 41.
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Patterns of expression of dauer-specific genes
We used a self-organizing map (SOM) to cluster the 1984 dauer-specific
genes into 45 groups, termed nodes, based on their patterns of expression
during the dauer exit and L1 starvation timecourses
[Fig. 3
(Kohonen, 1997); Cluster
Software (Eisen et al.,
1998
)]. Each row in Fig.
3 depicts the normalized expression profile of the genes contained
within that node.
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As in the case for feeding response, we compared each of the groups defined in these microarray experiments to groups of previously-defined functional classes to determine if some are significantly over-represented. We highlight some biological functions for each of the five expression categories. The complete set of over-enriched categories along with their relative enrichment are listed in Table 2.
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We observed that genes encoding cytochrome P450 enzymes and
UDP-glucuronosyltransferases are over-represented 3.2-fold
(P<0.001) and 4.9-fold (P<0.001), respectively, in the
dauer-enriched expression class. Cytochrome P450 enzymes are mono-oxygenases
that metabolize many endogenous and exogenous lipophilic compounds including
steroidal hormones, xenobiotics and fatty acids
(Mansuy, 1998).
UDP-glucuronosyltransferases attach sugar residues to lipophilic molecules
that facilitate their export from a cell
(Tukey and Strassburg, 2000
).
These enzymes might inactivate external contamination or internally generated
toxins, and thus provide stress resistance and perhaps prolonged lifespan for
dauers. In addition to stress and toxin resistance, both cytochrome P450
enzymes and UDP-glucuronosyltransferases could have a role in the metabolism
of a putative dauer entrance or exit hormone(s). Cytochrome P450 enzymes could
participate in synthesizing, modifying or degrading a putative dauer
hormone(s), while UDP-glucuronosyltransferases could regulate ligand activity
by decorating a putative hormone(s) with sugar moieties.
Dauer metabolism overview
Normal worms ingest bacteria for energy and biosynthesis components.
Carbohydrates and some derivatives of nucleic acids and amino acids are
metabolized through the glycolytic pathway into acetyl-coA (via pyruvate),
whereas lipids are metabolized by fatty acid ß-oxidation into acetyl-coA
(Stryer, 1995). Acetyl-coA is
subsequently metabolized by the tricarboxylic acid cycle (TCA, citric acid
cycle) and oxidative phosphorylation to generate ATP
(Stryer, 1995
). Thus, the
glycolytic, TCA, oxidative phosphorylation and fatty acid ß-oxidation
pathways are all active in normal worms. With respect to biosynthesis, many
building blocks can be obtained by ingestion. For example, nucleic acids and
amino acids can be directly recycled for RNA and protein synthesis.
By contrast, the dauer is non-feeding and must rely on internal reservoirs
for energy and biosynthesis. Fat is the major source for energy and
biosynthetic precursors in dauers, and accumulates in the intestine and
hypodermis during dauer formation. Fat is predominantly found in the form of
triacylglycerides, consisting of three fatty acids attached to a glycerol
backbone. As in normal worms, energy generation involves metabolizing
acetyl-coA (derived from fatty acids) via the TCA cycle and oxidative
phosphorylation. However, in dauers, fat must also provide biosynthetic
precursors. This can be achieved in part through fatty acid ß-oxidation,
the glyoxylate cycle and gluconeogenesis
(Stryer, 1995).
Dauer-enriched genes confirm metabolic predictions
The microarray data provide supporting evidence that all three of these
metabolic pathways are active in the dauers. First, we find that genes
encoding fatty acid ß-oxidation enzymes are dauer enriched (data not
shown). Previous results had shown that the specific activities of the enzymes
involved in fatty acid ß-oxidation are high in dauers, although at levels
lower than adults, indicating that lipids are an important energy reserve for
dauers (O'Riordan and Burnell,
1990). Our results support the importance of fat reservoirs in
dauers, and furthermore, identify the genes that encode the dauer-enriched
ß-oxidation isoenzymes (data not shown). Because glycerol is the backbone
for triacylglyceride fats, metabolism of fat for energy also implies
concurrent metabolism of glycerol for energy. Glycerol can be used for energy
generation after conversion into glyceraldehyde-3-phosphate, a metabolic
intermediate of glycolysis, by two enzymes: glycerol kinase and
glycerol-3-phosphate dehydrogenase. The microarray results show that R11F4.1
(3.9-fold, P<0.001), which encodes glycerol kinase, and K11H3.1
(2.8-fold, P<0.001) and F47G4.3 (3.6-fold, P<0.002),
each of which encodes glycerol-3-phosphate kinase, are dauer enriched. The
upregulation of both enzymatic activities for metabolizing glycerol in dauers,
as inferred from transcriptional upregulation, further supports the importance
of fat reserves in dauers.
Second, the microarray data indicate that the glyoxylate cycle is active in dauers. We see that expression of C05E4.9, which encodes the C. elegans bi-functional glyoxylate enzyme, is higher in dauers relative to the end of the timecourse (13-fold; P<0.001). Furthermore, F54H12.1 (aconitase), F48E8.3 (succinate dehydrogenase) and F46E10.10 (malate dehydrogenase) are more abundantly expressed in the dauer relative to the end of the dauer exit timecourse (Fig. 4; Table 3). Thus, we observe that the genes encoding four of the five enzymatic activities of the glyoxylate cycle are enriched in dauers suggesting that there is a greater capacity to metabolize fatty acids via this pathway. Furthermore, as there is more than one isoenzyme for aconitase and succinate dehydrogenase, we may have identified the genes that encode the glyoxylate cycle-specific isoenzymes.
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There are three essentially irreversible enzymatic steps in glycolysis
(those catalyzed by hexokinase, phosphofructokinase and pyruvate kinase), and
the microarray data show that the genes that encode all three of these steps
are enriched in dauers. Specifically, F14B4.2 (hexokinase, 1.7-fold,
P<0.003), C50F4.2 (phosphofructokinase, 5.5-fold,
P<0.001) and ZK593.1 (pyruvate kinase, 2.2-fold,
P<0.001) are enriched in dauers relative to 12 hours after dauer
exit (Fig. 5). Increased
expression of phosphofructokinase gene expression in dauers is consistent with
previous results (O'Riordan and Burnell,
1989). These data indicate that flux through glycolysis may be
higher in dauers relative to the end of the dauer exit timecourse. The two
major sources of glucose for glycolysis are extracellular or derived from the
breakdown of glycogen. Because the genes that encode enzymes of glycogen
metabolism are not upregulated in dauers (data not shown), extracellularly
derived glucose may be the primary substrate for glycolysis
Glycolysis and gluconeogenesis are competing processes that are both shown
to be enriched in dauers in the dauer exit timecourse microarray experiments.
As co-expression of both metabolic pathways would generate a futile cycle, it
is possible that cells expressing glycolytic enzyme activity are different
from those that express the gluconeogenic enzymes. For example, fatty acids
are stored in the intestine and epidermis of dauers
(Ogg et al., 1997). Glucose is
generated from fatty acids via gluconeogenesis in these tissues and may be
transported to other tissues, such as neurons and muscles, and serve as an
energy source. Tissues receiving glucose from the intestine and hypodermis
would be active in glycolysis for energy production. Alternatively, increased
mRNA levels might not reflect enzymatic activity as some glycolytic and
gluconeogenic enzymes are under allosteric regulation
(Stryer, 1995
). For example,
the gluconeogenic enzyme FBP activity is under tight metabolic allosteric
control (Stryer, 1995
). We
found that K07A3.1, which encodes FBP, is 2.3-fold dauer-enriched but
previously, FBP enzyme activity had been shown to be low in dauers relative to
adults (O'Riordan and Burnell,
1989
).
Gene expression mountains that are over-represented in the
dauer-enriched gene class
Five mountains are over-represented by the dauer-enriched gene class upon
comparison to the expression topomap: mounts 6, 8, 15, 21 and 22
(Table 2). Neuronal genes are
over-represented in mount 6 (Kim et al.,
2001), suggesting that other genes in this mountain may also have
neuronal function. Dauers display different behaviors than non-dauers, such as
seeking different temperatures, crawling up objects, projecting their heads
into the air and waving it back and forth, perhaps to permit attachment to
passing insects and allow transportation to more fertile soil
(Riddle, 1988
). The
dauer-enriched genes in mount 6 could be expressed in neurons and act to
modify these dauer-specific behaviors.
We examined the expression profile of all the genes in each of the over-represented mountains in the dauer exit timecourse. The overlap between the dauer-enriched gene class and mount 15 is particularly interesting. Mount 15 contains a total of 247 genes, of which 65 genes were selected from the microarray experiments as dauer-enriched using stringent statistical criteria (P<0.001). We found that essentially all of the genes in mount 15 are dauer enriched (Fig. 6B), suggesting that in addition to the 65 genes previously selected from the dauer exit timecourse, the other 182 genes in mount 15 are likely to be dauer enriched, although at a level below the one used in our stringent selection.
Genes in mount 15 are both aging and dauer regulated, as they are expressed
at higher levels in old versus young adults and in dauers versus non-dauer
worms (Lund et al., 2002). The
dauer animal is considered essentially to be non-aging, as they do not appear
to senesce (Klass and Hirsh,
1976
). Hence, mount 15 may identify a subset of aging and
dauer-regulated genes involved in a common mechanism to prolong life and delay
senescence.
Most of the genes in mount 22 appear to be dauer enriched. However, this result is probably an artifact of adult carcasses contaminating the dauer populations used in the timecourse experiments, as the genes in mount 22 do not appear to be dauer enriched using a pure population of dauers (see Materials and Methods; see supplemental tables at http://dev.biologists.org/supplemental/ and at http://cmgm.stanford.edu/~kimlab/dauer/).
Transient
The expression of transient genes peaks around two hours after introduction
of food and then declines (Fig.
3). The expression of these genes peak after change in surface
lipophilicity (about 30 minutes) and commitment to exit (about 1 hour), but
before many morphological and behavioral changes, such as pharyngeal pumping
(about 3 hours) and increase in the diameter of the worm
(Cassada and Russell, 1975;
Golden and Riddle, 1984
;
Proudfoot et al., 1993
). These
genes could be an early transcriptional response that sets up the dauer
recovery process. In order for dauer recovery to be successful, all of the
cells in an animal must exit the dauer stage synchronously. One plausible
mechanism to coordinate dauer exit would be via distribution of a hormone(s)
throughout the entire body. We see four gene classes that may regulate the
synthesis and distribution of a hormone important for dauer recovery.
First, genes encoding cytochrome P450 enzymes are over-represented in the
transient class of dauer exit genes (Table
2). There are 81 cytochrome P450 genes in the genome, and eight of
these are transient genes in the dauer exit timecourse (5.6-fold
over-representation, P<0.001). Cytochrome P450 enzymes are
mono-oxygenases that metabolize many endogenous and exogenous lipophilic
compounds including steroidal hormones, xenobiotics and fatty acids
(Mansuy, 1998). The cytochrome
P450 enzymes and perhaps other biosynthetic enzymes could synthesize a dauer
exit hormone(s). daf-9 encodes a cytochrome P450 involved in
regulating dauer development (Antebi et
al., 2000
; Gerisch et al.,
2001
; Jia et al.,
2002
). The microarray experiments show that daf-9
expression increases early and then remains high during the dauer exit
timecourse.
Second, genes encoding UDP-glucuronosyltransferases are over-represented in
the transient class of dauer exit genes. There are 73
UDP-glucuronosyltransferase genes in the genome, and four of these are
transient genes in the dauer exit timecourse (4.9-fold over-representation,
P<0.001). UDP-glucuronosyltransferases facilitate the export of
lipophilic molecules by attaching sugar residues
(Tukey and Strassburg, 2000).
UDP-glucuronosyltransferases could function within the signaling cell by
conjugating a sugar residue to a putative dauer exit hormone, thereby
facilitating its export and distribution to the rest of the body.
Alternatively, they might function within the receiving cell as an initial
cellular response to attenuate the hormonal signal.
Third, genes encoding transporters are over-represented in the transient
class of dauer exit genes. There are 407 transporter genes in the genome, and
13 of these are transient genes in the dauer exit timecourse (2.9-fold
over-representation, P<0.001). Transporters facilitate the
movement of molecules across cell membranes. Of the genes encoding
transporters in the transient gene class, four encode members similar to the
multidrug resistance protein family. The multidrug resistance proteins are a
family of transporters that are often elevated in expression in cells
resistant to toxic compounds (e.g. multidrug resistant cancer cell lines)
(Dean et al., 2001). The
physiological role of some multidrug resistance proteins include transporting
steroidal and lipophilic signaling molecules
(Dean et al., 2001
). One of
the transporters, pgp-1, is implicated in arsenite and cadmium
resistance, while the specific functions of the other three transporters
(F14D7.6, T21E8.1 and T21E8.2) are unknown and could be to export a dauer-exit
hormonal molecule (Broeks et al.,
1996
).
Fourth, genes encoding nuclear hormone receptors are over-represented in the transient class of dauer exit genes. There are 270 nuclear hormone receptor genes in the genome, and 10 of these are transient genes in the dauer exit timecourse (3.3-fold over-representation, P<0.001). Nuclear hormone receptors are ligand-activated transcription factors that are involved in many diverse process such as metabolic regulation, sexual differentiation and embryonic development. The large number of induced nuclear hormone receptors present in the transient class of dauer exit genes might reflect redundant functions, cell- or tissue-specific expression, a specific function for each nuclear hormone receptor or a combination of these possibilities.
daf-16 encodes a Forkhead transcription factor and is a member of
the transient gene class (Ogg et al.,
1997). daf-16 promotes dauer formation and functions
downstream of the daf-2/insulin-like receptor signal transduction
pathway that regulates dauer development and longevity
(Dorman et al., 1995
;
Tissenbaum and Ruvkun, 1998
).
daf-16 has at least three alternatively spliced forms designated
daf-16a1, daf-16a2 and daf-16b. The Forkhead DNA binding
domains of DAF-16a and DAF-16b are highly related but distinct.
DAF-16B but not DAF-16A is expressed in the pharynx and is required for
pharynx remodeling during dauer formation
(Henderson and Johnson, 2001;
Lee et al., 2001
;
Lin et al., 2001
;
Ogg et al., 1997
). Our
microarray data show different expression kinetics for the different
daf-16 isoforms; specifically, daf-16a is transiently
induced, whereas daf-16b decreases expression during the dauer-exit
timecourse. There are three spots on the microarray that correspond to
different regions of daf-16: R13H8.2, R13H8.1 and DAF-16#2. R13H8.2
hybridizes to daf-16a but not daf-16b and exhibits transient
kinetics in the dauer exit timecourse (Fig.
7). R13H8.1 and DAF-16#2 hybridize to both daf-16
isoforms and are downregulated during the dauer exit timecourse. These results
suggest that daf-16a may have both dauer formation and dauer recovery
functions, whereas daf-16b might be important for the maintenance of
some aspect of the dauer state (e.g. the pharynx).
|
Early
Early genes are induced early in the dauer exit timecourse, and then remain
induced (Fig. 3). Genes that
are expressed early in dauer exit could be required for resumption into an
active state from a quiescent one. For example, normal worms eat and digest
food to generate energy for sustenance and growth. Proteases and acid
phosphatases (in the other phosphatases gene group) are involved with
digestion and are over-represented 3.3- and 5.3-fold in the early gene class
(Table 2). There is also an
increase in sugar and amino acid transporters (2.9-fold over-represented,
Table 2) that may function in
food uptake.
Genes that encode six ABC transporters/multidrug resistance family proteins
are found in the early gene class: mrp-2, pgp-3, C44B7.8, T28C12.2,
W04C9.1 and ZK484.2. One gene (C44B7.8) encodes a peroxisomal ABC transporter
that specifically transports long-chain fatty acids across the peroxisomal
membrane for fatty acid ß-oxidation. Two (mrp-2 and
pgp-3) are involved in toxic metal ions or cholchine/chloroquine
resistance (Broeks et al.,
1996; Broeks et al.,
1995
). The precise function of the remaining three genes is
unknown. Worms ingest potential toxins as they exit the dauer state. These
three ABC transporter/multidrug resistance family proteins could export a
variety of these toxic molecules, and thereby confer resistance to them.
Climbing
Climbing genes have continually increasing expression during the dauer exit
timecourse (Fig. 3). The
transient and early genes that encode regulatory proteins such as
transcription factors might control, directly or indirectly, the expression of
genes in the climbing class.
Energy is generated from food through the glycolytic, tricarboxylic acid cycle (TCA), fatty acid oxidation and oxidative phosphorylation pathways. We observed that genes involved in these pathways are over-represented in the climbing gene class (Table 2): glycolysis (6.5-fold), TCA (9.1-fold), fatty acid oxidation (4.8-fold) and mitochondrial (4.6-fold) gene classes. The mitochondrial gene class includes the oxidative phosphorylation enzymes that are important for ATP generation. All of these biological gene groups would also be expected to be required during the L1 starvation timecourse. In general, these biological gene groups are regulated in both the dauer exit and L1 starvation timecourses, but to a different extent or with different kinetics.
Late
The late genes are induced just before the dauer-to-L4 molt in the dauer
exit timecourse. Collagens are expressed in preparation for a molt in order to
synthesize cuticle for the next larval stage. We find collagen genes to be
over-represented 12-fold in the genes showing late kinetics during dauer exit
(Table 2). Other genes
associated with cuticle or collagen processing are also expressed at this
time. For example, M153.1 encodes a pyrroline-5-carboxylate reductase (which
catalyzes the final step in proline biosynthesis) and is expressed at a late
time during dauer exit. This is consistent with increased collagen
biosynthesis as proline is abundant in collagens.
The C. elegans genome does not encode a homolog to Drosophila
hedgehog (hh). However, it does encode 46 genes that are
distantly related to hh called, warthog (wrt-1 to
wrt-10), groundhog (grd-1 to grd-14) and
ground-like (28 grl genes)
(Aspock et al., 1999) (see
supplemental Fig. S3 at
http://dev.biologists.org/supplemental/
and at
http://
cmgm.stanford.edu/~kimlab/dauer/). Ten wrt, grd or
grl genes are present in the late gene set, corresponding to a
12-fold enrichment that is statistically significant (hypergeometric,
P<0.001). In flies and vertebrates, members of the hh
family encode secreted signaling molecules important for anteroposterior
patterning and cellular differentiation events
(Hammerschmidt et al., 1997
),
although in C. elegans the function of wrt, grd and
grl genes is unknown. Our data suggest that some of the wrt,
grd and grl genes may function during the dauer-to-L4 molt or
during molting in general (see supplemental Fig. S3 at
http://dev.biologists.org/supplemental/
and at
http://cmgm.stanford.edu/~kimlab/dauer/).
hh signaling leads to increased ptc transcription
(Marigo et al., 1996). Seven
Patched-related/Niemann-Pick type C (NPC)-related genes, corresponding to
17-fold over-representation (hypergeometric, P<0.001), are found
in the late group. These data support the possibility that the C.
elegans Patched-related/NPC-related genes might be transcriptionally
activated by wrt, grd and grl signaling. Alternatively,
human NPC1 is implicated in retrograde sterol transport from lysosomes
(Neufeld et al., 1999
), so
increased expression of these seven genes may reflect an increased need to
mobilize cholesterol or its derivatives at this time.
Three mountains on the expression topomap are over-represented among genes
showing late kinetics during dauer exit: mounts 14, 16 and 29. Mount 16 is
enriched in muscle genes and collagen (Kim
et al., 2001). There are 49 genes in the late class that are also
part of mount 16. Of these, 31 are collagen genes. The remaining 18 genes
might function in association with collagens or in muscle. No common
biological function was previously noted for genes in mount 29. We plotted all
the genes in mount 29 in the dauer exit and L1 starvation timecourses, and
found that nearly all were induced at the dauer-L4 (or L3-L4) molt
(Fig. 6D). This result suggests
that genes in mount 29 may be involved in these molts. The genes in mount 14
show a heterogeneous expression response in the dauer exit and L1 starvation
timecourses (Fig. 6A).
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DISCUSSION |
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Comparison to SAGE analysis
The dauer larvae transcriptional profile has also been analyzed using
serial analysis of gene expression (SAGE)
(Jones et al., 2001). By
comparing the transcript tag abundances found in dauer with that of a
mixed-staged population, Jones et al. identified a set of 358 dauer-specific
tags (P<0.05). Of these, 305 are present on the DNA microarrays
used in the experiments from this paper, and 43 (14%) overlap with the 540
dauer-enriched genes defined by our criteria. Hence, there is a poor overlap
between the SAGE data and dauer-enriched genes identified by our microarray
data. One possibility for the poor agreement is that the SAGE experiment
selected genes with a lower stringency than the DNA microarray experiments
(P<0.05 in the SAGE dataset versus P<0.001 in the
microarray dataset). A more stringent criteria of P<0.001 for the
SAGE dataset requires at least eight dauer-specific tags and corresponds to 53
dauer-specific genes. However, only 20 out of the 53 genes selected by SAGE
(38%) are also selected by the microarray analysis. Second, the source of
dauer larvae is different in the two experiments; the SAGE experiments
prepared dauers from liquid cultures, whereas the microarray experiments
prepared dauers from agar plates. Third, the experimental design and analysis
were different; the SAGE experiments defined a set of dauer-specific genes by
comparing dauers to mixed-staged animals, while the microarray experiments
defined a set of dauer-enriched genes using a dauer exit timecourse. Finally,
the SAGE analysis was performed using only one biological sample, whereas we
repeated our experiments using eleven time points from four independent
timecourses. Thus, some of the dauer-specific genes identified by the SAGE
experiment may not be reproducible in other samples of dauers.
Evaluating gene expression changes
In addition to functioning in the dauer itself, the dauer-enriched genes
may be expressed in dauers in preparation for exit to normal development. As
the primary survival strategy of C. elegans is to propagate
successfully as often as possible, exiting the dauer state rapidly and
efficiently may be important. The pre-dauer animal may express a stored mRNA
pool in preparation for dauer recovery. Consistent with this, transcriptional
inhibition does not prevent the initiation of dauer recovery
(Reape and Burnell, 1991).
Global transcription is depressed in the dauer larvae but increases
dramatically upon exit (Dalley and Golomb,
1992). The microarray experiments assay changes in mRNA levels for
one gene relative to other genes in the sample, and does not measure changes
in absolute mRNA levels. Hence, genes that show increased expression in the
microarray analysis are those that induce expression even more than would be
expected due to the global increase in expression during dauer exit.
Conversely, genes that show decreased expression in the microarray analysis do
so relative to the general increase exhibited by the rest of the genome. These
genes may maintain steady state levels or even show small expression increases
that are smaller than the general level of increase in mRNA accumulation.
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ACKNOWLEDGMENTS |
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![]() |
Footnotes |
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