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Physiol. Genomics 25: 134-141, 2006. First published January 10, 2006; doi:10.1152/physiolgenomics.00262.2005
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Received 20 October 2005; accepted in final form 4 January 2006.
Physiological Genomics 25:134-141 (2006)
American Physiological Society © 2006 American Physiological Society

Identification and function of hypoxia-response genes in Drosophila melanogaster

Guowen Liu , Julianne Roy and Eric A. Johnson

Institute of Molecular Biology, University of Oregon, Eugene, Oregon


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Hypoxia, an insufficient level of oxygen in the cell, occurs during normal activity and also in pathological conditions such as ischemia and tumorigenesis. Although many hypoxia-response genes have been identified, an understanding of the functional role for these genes in the living animal is lacking. Here we present a genome-wide study of gene expression changes during hypoxia and then functionally test a subset of these genes for roles in survival and recovery from hypoxia. We found 79 genes with increased mRNA levels when adult flies were treated with 0.5% O2 for 6 h. A subset of these genes had detectably increased levels in as short as 1 h of low-oxygen treatment. Mild hypoxia levels resulted in an increase in transcription levels for only 20 genes. Viability during hypoxia and recovery time from hypoxia-induced paralysis was examined in flies with a reduction in activity in hypoxia-response genes. The observed decreased viability and increased recovery time from paralysis in many of the lines demonstrate that the increased transcript levels seen after hypoxia are important for the response to low oxygen.

gene expression; microarray; low oxygen; paralysis; viability


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
WHEN FACED WITH INADEQUATE oxygen (hypoxia), animals undergo a series of transient and long-term changes to increase their access to oxygen and decrease their need for it. If oxygen homeostasis is not restored, death or serious tissue damage can result. In humans, hypoxic damage to heart and brain tissue is the proximate source of pathology in heart attacks and strokes (20). Serious pathology can also result when the hypoxic responses are inappropriately activated, such as with rapidly proliferating tumors in which VEGF is expressed, attracting new blood vessels to proliferate and supply the tumor with oxygen (4, 19). Much of what is known about hypoxia-sensing and -response pathways on the molecular level has come from biochemical studies of cultured mammalian cells. A key breakthrough was the identification in 1993 of a transcription factor complex, called hypoxia-inducible factor 1 (HIF-1) (22, 23). HIF-1 was found to cause the hypoxia-dependent expression of erythropoietin by binding to its regulatory region in low-oxygen conditions. HIF-1 has since been found to upregulate many hypoxia-response genes, as varied as VEGF and glycolytic pathway genes (7).

Many genes are regulated by hypoxia and, in particular, by HIF-1 activity. These genes carry out a wide range of functions to adapt the cell to decreased oxygen availability. Some hypoxia target genes are expressed in virtually all cells to regulate cellular metabolism. For example, hexokinase, an enzyme acting in the glycolytic pathway, is induced by HIF-1 and hypoxia to metabolize glucose under anaerobic conditions (16). Other genes are hypoxically regulated in particular tissues to fulfill a specialized requirement of that organ. HIF-1 upregulates VEGF in hypoxic tissue to initiate the process of angiogenesis, the growth of blood vessels (8, 13, 17). Although key genes controlling some hypoxia responses have been identified, the full complement of hypoxia-response genes remains unknown.

The combination of genetics with genomics has proven to be a valuable tool for identifying genes regulated by HIF-1 in low oxygen. A viable HIF-1{alpha} mutation in Caenorhabditis elegans has allowed gene expression studies to be performed on whole animals in normal- and low-oxygen conditions (21). Of the 110 hypoxia-regulated genes identified, 63 required HIF-1 activity. In mammalian model systems such as mice, knockouts of HIF-1{alpha} have led to embryonic lethality, making experimental manipulation more difficult. However, heterozygous HIF-1 knockouts and tissue-specific knockouts can survive and have some impairment in the hypoxic response (11, 12). Significant progress has been made in understanding the molecular pathways that shape the response to hypoxia in Drosophila. There are homologs to both subunits of the HIF-1 transcription factor complex, the VHL gene that mediates interactions with the proteasome and a HIF-1 prolyl hydroxylase to mark HIF-1{alpha} for degradation (3, 14, 18). Genetic screens have been used to find mutants that have a lengthened waking period from 0% O2, an effect that has been useful in selecting for neuron-specific anoxia protection genes (9). For example, mutations in trehalose phosphate synthase increased recovery time needed after anoxia, whereas overexpression shortened recovery (6). Significantly, trehalose phosphate synthase expression in mammalian cells confers protection to mammalian cells as well as in Drosophila (5).

Here we examine on a global scale increased transcript abundance during hypoxia. We find that large numbers of genes have increased transcript abundance during severe hypoxia and that a subset of these genes' transcripts is also more abundant at an early time point and during mild hypoxia. We provide confirmation by RT-PCR that the microarray results reflect actual changes in transcript abundance. More importantly, we provide genetic evidence that the regulation of transcript abundance has functional consequences. Flies with a reduced dosage of many hypoxia-response genes have increased death during hypoxia and require increased time to become active after exposure to low oxygen.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Fly lines.
Oregon R and Sb/Tm3 were the fly lines used for identifying hypoxia-response genes by microarray. Mutant fly lines for hypoxic genes [Bloomington stock nos. 513 and 514 (hairy), 13953 (CG18135), 14047 (ade5), and 4548 (astray)] were used to study changes in viability and/or recovery from hypoxia treatment.

Microarray printing and postprocessing.
A gene expression microarray with 21,000 spots (~16,000 spots from PCRs of predicted open reading frames from Incyte Genomics and ~5,000 from DGC cDNA clones from BDGP) were printed on poly-L-lysine-coated slides and after postprocessing were used for hybridization as in Ref. 1.

DNA microarray hybridization.
Independent pairs of fly populations in vials (each had 50 5-day-old adult flies: 25 males and 25 females) were treated with normal or low oxygen. In each pair (randomly picked from the same population in a bottle), one was left under normoxia and the other was put in an upside-down 2-liter beaker partly submerged in water and aerated with gas of 0.5% O2-99.5% N2 or 5% O2-95% N2 for 1 or 6 h. Repeated experiments were performed at the same time of the day to reduce differences due to circadian effects. After exposure, flies were quickly collected into tubes merged in liquid nitrogen. Total RNA of each collection was extracted with TRIzol reagent according to the manufacturer's instructions (Invitrogen). For each microarray hybridization, ~30 µg of the total RNA from each sample was labeled by incorporation of Cy3- or Cy5-dUTP (PerkinElmer) into newly synthesized cDNA by a 2-h reverse transcription reaction with Superscript II reverse transcriptase (Invitrogen). After RNase H treatment, a Cy3-dUTP-labeled cDNA population was mixed with a Cy5-dUTP-labeled population, purified with a QIAquick PCR purification kit (Qiagen), and resuspended in 4x SSC, 1.5 mg/ml poly A, and 0.3% SDS solution. After boiling for 2 min and a cooldown for 30 s by a brief spinning in a microcentrifuge, the labeled cDNA mixture was loaded onto a microarray slide (custom spotted array with amplified genomic DNA with the Incyte Genomics Drosophila open reading frame primer set), covered with a coverslip, put into a hybridization chamber (Corning), and hybridized in a 65°C water bath for ~16 h. After washing, the microarray slide was scanned with a Genepix 4000B scanner (Axon Instruments) and data were analyzed as described below.

Microarray data analysis.
We wished to identify genes with strongly changed expression. The microarray data were analyzed in Microsoft Office Excel. Microarray spots that were blank, very faint, or saturated were first filtered. After subtraction of backgrounds, the signals from green (F532 median) and red (F635 median) channels of each spot were first changed into their logarithms (for a sample of the data distribution from a microarray, see Fig. 1A), and then a regression was calculated between the two series data [Lg(F635) and Lg(F532)]. The calculated intercept and X variable were used to build a new reference system where the x-axis is the regression fit line of the data, representing the average signal strength, and all the data (LgF635 and LgF532) were then transformed into this new reference system (Fig. 1B). The y-axis indicates the deviation of a spot from the average of all spots. After a second regression with these transformed data, a second new reference system with the new fit line as its x-axis was built and all the data were transformed for a second time (Fig. 1C). The second regression and transformation slightly further improved the fitness of the x-axis (compare Fig. 1, B and C). Every spot was then further centered in reference to the average of its surrounding spots (100 spots immediately at its left and 100 spots immediately at its right). The standard deviation of these 200 spots surrounding each spot was calculated, and the deviation of each spot was normalized after dividing by its standard deviation (called normalized deviation; Fig. 1D). The normalized deviation of each spot was used to indicate the degree of the expression difference of a gene between the two RNA samples.


Figure 1
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  		Fig. 1. Dot plots of microarray hybridization data between a hypoxic fly RNA and its corresponding normoxic RNA to illustrate the method of data analysis. After blank, faint, and saturated spots were filtered out, the signals from green (F532 median) and red (F635 median) channels of each spot were first changed into their logarithms (A). A regression was then calculated between the 2 data series (LgF635 and LgF532). A new reference system was built in which the x-axis is the regression fit line of the data. All data (LgF635 and LgF532) were then transformed into this new reference system, in which the x-axis represents the average signal strength and the y-axis indicates the deviation of a spot from the average of all spots (B). After a second regression with these transformed data, a second new reference system with the new fit line as its x-axis was built and all the data were transformed a second time (C). The second regression and transformation slightly further improved the fitness of the horizontal axis (compare B and C). Every spot was then further centered in reference to the average of its surrounding spots (100 spots immediately at its left and 100 spots immediately at its right). The standard deviation of these 200 spots surrounding each spot was calculated, and the deviation of each spot was normalized after dividing by its standard deviation (called normalized deviation) (D). The normalized deviation of each spot was used to indicate the degree of the expression change of a gene between the 2 RNA samples.

 
Eight independent repeats (RNAs extracted from different fly vials) of DNA array hybridizations were done for adult flies after 6-h treatment under 0.5% O2. In six of these, RNA of hypoxic flies (four from Oregon-R, two from Sb/Tm3) were Cy5-dUTP labeled and RNA from the corresponding normoxic flies were Cy3-dUTP labeled. In two repeats, fluorescent dyes were swapped for labeling: RNA of hypoxic flies from Oregon-R were Cy3-dUTP labeled, and RNA from the corresponding normoxic flies were Cy5-dUTP labeled. After data analysis, the normalized deviation of each gene was used to indicate the degree of change in transcript abundance. For each gene, if five or more of the eight repeats had values >1.70, this gene was identified as hypoxia regulated. If three or four of the eight repeats had values >1.70 and the average of all the available values was >2.5, the gene was also identified as hypoxia regulated. Many of the identified genes had within-experiment repeat spots that confirmed the inclusion in the hypoxia-regulated set.

Three independent repeats were carried out for wild-type Oregon-R flies to identify genes with increased transcript abundance after the treatment under 0.5% O2 for only 1 h and also after that under 5% O2 for 6 h. Data were analyzed as described for the 6-h treatment under 0.5% O2. If two or more of the three repeats had values >1.80 and the average of the three repeats was >1.70, this gene was regarded as hypoxia regulated. Because the goal of this study was to functionally test flies with reduced dosage of hypoxia-regulated genes, we only characterized genes with increased transcript abundance in hypoxia.

Microarray raw data files have been deposited with GEO to conform with MIAME standards and given accession number GSE3482.

Functional tests of hypoxia-induced genes on hypoxic recovery and survival.
Twenty-five males and twenty-five females (50 total) of each fly line were used for each recovery from hypoxia experiment. Flies were 5-day-old adults. Flies were exposed to 0.5% O2 for 16 h at 22°C and then removed from hypoxic conditions and put at normal oxygen conditions and observed for the time to recover from paralysis, as indicated by >20% of flies in the vial walking. Experiments were repeated three times.

For the viability studies of each fly line, 50 males and 50 females (100 total) were used for each experiment (age = 5 days old) for the single-mutant fly lines. The double-mutant fly lines had 15–55 total flies for each experiment. Flies were exposed to 0.5% O2 for 16 h at 25°C, and after hypoxia flies were moved to normal oxygen conditions and rates of survival were recorded after 24 h to allow for full recovery. Each line was tested two to six times in separate exposures to hypoxia.

Quantitative RT-PCR.
RT-PCR was performed for each gene with Superscript II (Invitrogen)-produced cDNA from total RNA extracted from Oregon R flies left at normal oxygen conditions (normoxia) and from Oregon R flies exposed to 0.5% O2 conditions for 6 h (hypoxia). Optimal PCR cycle numbers were individually determined for each gene. The expression levels of each gene in normoxic and hypoxic flies were visualized by agarose gel electrophoresis and quantified.

PCR conditions were 94°C for 2 min (94°C for 50 s, 55°C for 50 s, 68°C for 60 s) for the optimal number of cycles, 68°C for 10 min. Primers used were Arp87c fwd: GCCTTATGATGTCGTCGTCAACC, Arp87c rev: AGCCGAGTGTTTCTTCAGTTCG (26 cycles); ade5 fwd: AGATGTCCACCACCACAACAGC, ade5 rev: CCCAAATGAAGTTCCTCTTTACGG (26 cycles); astray fwd: TGGCACACACAAACCGTAACC, astray rev: CGTCGCTATTCTCCTTCCTTATCAG (32 cycles); Gst D21 fwd: TATCCCCTTTTCCGCACTGG, Gst D21 rev: AGTTCTCATCCCATCCTGGAGTC (28 cycles); Hairy fwd: ACTGTGTGAACGAGGTTAGCCG, Hairy rev: TGCGAGTTGGATGAGTTGTGG (30 cycles); CG1600 fwd: CATCGCCTCCTATCACTTTGCC, CG1600 rev: TGTAATCCGCTTCTGCTGGG (28 cycles); prx 2540 fwd: AACAGCAAGATGCGTTTGGG, prx 2540 rev: TGGGGAAGAGTTTATGAGCCTCC (30 cycles).

Gene family enrichment analysis.
We developed software to examine array data for enrichment in biological functions as defined by Gene Ontology (GO) (2). A web interface is at http://genomix.uoregon.edu/go/uploadgenes.php.

We used the FB (Flybase) database, with parameters enrichment cutoff = 5, Monte Carlo false positive cutoff = 0.05, and Monte Carlo sets = 1,000. The number of genes with GO annotations in the array set was determined, and then for every node of the GO tree the number of genes in the array set included in that node was compared with the number of genes in the entire database included in the node. This ratio is the enrichment. To determine the statistical significance of the enrichment, random sets of genes equal to the number of array genes were selected from the database and the number of times that a random set had an equal number or greater of genes included in the GO node was the false positive rate.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
We investigated the response of adult Drosophila melanogaster to low-oxygen stress by exposing flies to 0.5% O2 for 6 h. This amount of oxygen produces a strong hypoxic stress, as lengthy exposure (>16 h) produces lethality in adults. Gene expression was measured by hybridizing labeled cDNA derived from total RNA to a custom spotted array comprising nearly all predicted genes in the genome. For each experiment, low-oxygen-exposed flies and flies reared in identical conditions except that they were exposed to normal (21%) oxygen were compared by competitive hybridization. Eight repeats of the experiment were performed, including two experiments in which the exposed and control flies were dye-swapped to control for differential incorporation artifacts. These experiments identified 79 genes with strongly and significantly (MATERIALS AND METHODS) increased transcript abundance after hypoxia (Table 1).


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  		Table 1. Genes with increased abundance after 6 h in 0.5% O2

 
Sets of genes with related biological functions were upregulated by hypoxia exposure. We systematically searched the set of upregulated genes for enrichment in particular cellular functions as defined by the GO hierarchy. Monte Carlo simulation was used to find all GO groups that were enriched in the hypoxia set compared with random sampling. We filtered the functional groups for those that were at least fivefold overrepresented with a false positive rate of P < 0.05 to identify meaningful enrichments in gene representation. We found that multiple cellular functions are coordinately regulated in hypoxia. Some responses to hypoxia were not surprising, such as oxygen and reactive oxygen species metabolism, electron transporter activity, or peroxidase activity. Of interest was the enrichment of genes involved in other stress responses, such as the immune response, response to heat, and response to toxins. Thus the hypoxia response activates suites of genes that carry out diverse functions within the cell.

We compared the change in expression after 6 h of 0.5% O2 to shorter exposures and milder conditions. First, we hybridized in triplicate experiments RNA from adults exposed for 1 h in 0.5% oxygen to microarrays. At this shorter exposure, only 20 genes had significantly increased transcript abundance (Table 2).


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  		Table 2. Genes with increased abundance after 1 h in 0.5% O2

 
Flies in 5% O2, a milder hypoxic stress, were also assayed for changes in transcript abundance. Adult flies exposed to 0.5% O2 quickly become motionless for the duration of the low-oxygen condition, but flies remain moving during exposure to 5% O2. Only 47 genes showed a significant increase in transcript abundance over a 6-h period in 5% O2 (Table 3) compared with the 79 genes found to have increased abundance in 0.5% O2. Thirteen of the genes were in common between the two conditions. Those genes showing changed expression only in 5% O2 were enriched in glucose transport, carbohydrate metabolism, and electron transporter activity. Heat shock proteins (HSPs) were not induced in the milder hypoxia condition, suggesting that the gene expression changes are helping to adapt the fly to low oxygen rather than as a response to acute stress.


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  		Table 3. Genes with increased abundance after 6 h in 5% O2

 
Semiquantitative RT-PCR was used to confirm the increased transcript abundance in genes identified by the microarray data. Primers were designed to amplify the coding region of the tested genes. All the genes tested showed a higher level of transcript abundance in flies in hypoxic conditions (0.5% O2 for 6 h) compared with flies in normoxic conditions, thus validating our results from the microarray experiments (Fig. 2).


Figure 2
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  		Fig. 2. Validation of transcript abundance changes with semiquantitative RT-PCR. A: agarose gel photos of RT-PCR products that compare transcript levels of particular genes (name listed below each pair) during normal oxygen (–) and hypoxic (+)conditions. There is an increase in transcript abundance during hypoxia (0.5% O2 for 6 h) compared with normoxia for several genes, confirming microarray data of increased transcript abundance. Arp87c is a control gene with an equivalent abundance of transcripts during both normoxia and hypoxia. B: quantification of RT-PCR products comparing normoxia (open bars) to hypoxia (filled bars) for each gene.

 
Gene expression changes during low-oxygen stress are thought to adapt cellular functions to the changed environment. Therefore, the hypoxic genes identified at a whole animal level would be expected to contribute to a better survival of this organism. We examined the functional role of hypoxia-induced genes by assaying recovery from paralysis (10) and overall viability in low oxygen in flies. First, 5-day-old adult flies with a reduced dosage (either homozygous hypomorphic alleles or heterozygous null alleles) of hairy, ade5, astray, and CG18135 were placed at 0.5% O2 for 16 h at 22°C. Also included were Oregon-R, w1118, and a balancer line (Sb/TM3) as controls. Flies with a reduced dosage of a hypoxia-induced gene took >2.5-fold longer to begin walking than the longest to recover control (see Fig. 3A). These differences were repeatable in more than five repeated experiments. Thus the hypoxia-response genes are needed for efficient recovery from exposure to low oxygen.


Figure 3
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  		Fig. 3. Functional testing of genes with changed transcript abundance during hypoxia. A: time of revival from hypoxic paralysis (stupor) after removal from hypoxic conditions. Filled bars are control fly lines, and gray bars are mutant fly lines being tested. Wild-type flies (Oregon-R and w[1118]) and the random mutants (Prm[10631] and CG10365[KG00107]) took 2–10 min for 20% of the population to resume walking, whereas heterozygous gene mutants ade-5, astray (aay[S042314]), CG18135, and hairy (h[1] and h[2]) required 20–50 min. Flies received hypoxia treatment of 16 h of 0.5% O2 (22°C) and then were moved to normal oxygen conditions to test time before revival. Error bars are SE for the 3 repeated experiments. **With a t-test comparing the recovery time for the mutant fly line to the combined control fly recovery times, the difference in recovery is observed to be significant (P < 0.001). B: rates of survival of fly lines after exposure to 0.5% O2 for 16 h at 25°C. Filled bars are control fly lines, and gray bars are fly lines with mutations in genes found to be regulated during hypoxia. Flies with mutations in genes upregulated during hypoxia, hairy (h[1]), astray (aay[S042314]), thread (th[4]), vrille (vri[K05901]), and ade5, do not survive hypoxic conditions as well as control flies (w[1118] and others). Rating values are as follows: 4 = 80% or more alive and very active, 3 = 51–80% alive, 2 = 21–50% alive, 1 = 1–20% alive, 0 = no survivors. Error bars represent SE. C: rates of survival of fly lines after exposure to 0.5% O2 for 12 h at 25°C. Filled bars are control fly lines, and gray bars are fly lines with mutations in genes found to be regulated during hypoxia. Double heterozygous mutant flies do not survive hypoxic conditions as well as control flies. Control fly lines are heterozygous for single mutations. Rating is the same as in B.

 
Survival of flies with a reduced dosage of hypoxia-response genes was also examined. Five-day-old adult flies were placed at 0.5% O2 for 16 h at 25°C. Wild-type control lines had good survival under those conditions, with >60% of the flies active after 24 h of recovery. Seven of the seventeen tested mutant lines had >60% of the flies survive as well, indicating that loss of one copy of those hypoxia-response genes had no effect on overall function. Of the remaining 10 lines, 5 had 30–60% viability and 5 had <30% viability (Fig. 3B). Thus a reduction in gene dosage in a majority of tested genes caused a reduction in viability during hypoxia.

We next tested whether the reduced dosage of hypoxia-induced genes could further decrease viability when flies were made heterozygous for two genes. We chose two lines that showed effects when the dosage was reduced, hairy and ade5, and crossed the lines to each other or to a control line. Progeny from these crosses were exposed to a less severe hypoxic stress, 12 h of 0.5% O2 at 25°C, and then examined for viability. The flies produced from control crosses (hairy/control or ade5/control) had >80% survival. Flies doubly heterozygous for hairy and ade5 (ade5/+; hairy/+) had <30% survival (Fig. 3C). The additive effects suggest that multiple aspects of organismal function are being regulated by the hypoxic response.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
The results of this study describe the genetic basis of the response to hypoxia in Drosophila melanogaster. Most importantly, we demonstrate that genes regulated in response to hypoxia are required for survival during hypoxic stress. We also show that genes thought to be required in other stress responses are upregulated in hypoxia and that gene expression varies over time and according to the severity of the oxygen loss.

Although hypoxia-response genes have been identified in many species and in specific tissues, few studies have tested the importance of oxygen-regulated gene expression on the ability of the whole organism to survive hypoxic stress. Therefore, the extent to which hypoxia-induced genes are critical for survival is unclear. Drosophila is a useful system with which to determine the functional significance of expressed genes, because of the conservation of the HIF-1 pathway and the extensive genetic resources available. We have tested whether changes in transcript abundance are functionally important for the response to hypoxia by identifying a set of hypoxia-responsive genes with a whole genome cDNA array and then assaying the response of flies with only partial activity of those genes.

We saw a dosage-dependent requirement for the activity of many of the hypoxically induced genes in two different tests, one examining recovery from paralysis and the other examining survival. Screens examining the time to recover from hypoxia-induced paralysis have uncovered neuron-specific protective proteins such as fau (15), although genes involved in general cellular metabolism throughout the entire body may be required for recovery as well. We tested flies lacking one copy of hairy, ade5, astray, and CG18135, which were selected for representing a diverse set of functions (gene regulation, purine base metabolism, peripheral nervous system development, and unknown function), and having existing mutations available. All four lines required a longer period of time to regain activity after exposure to severe hypoxia, demonstrating that the increased transcript abundance of these genes during hypoxia is needed to mitigate the effects of low oxygen. The paralysis induced by hypoxia has been proposed to be the result of a loss of neuronal cellular function (15). We show that genes with diverse functions are required for recovery. This suggests that neuron function during hypoxia is sensitive to the activity of both neuron-specific and general cell metabolism genes.

A reduction in dosage of many of the hypoxia-induced genes was sufficient to impair survival. Ten of the seventeen lines tested had reduced rates of survival compared with control lines. This suggests that the regulation of gene expression is a crucial aspect of the response to hypoxia and that the precise level of expression is critical as well. Interestingly, a reduction in dosage in two genes at once (hairy and ade5) increased the sensitivity of the flies to hypoxia and resulted in even poorer viability compared with wild-type controls and siblings with only one or the other gene reduced in dosage. Because we looked at partial reductions in activity, we cannot make inferences about the relationship between the genes involved. However, as for the hypoxia recovery experiment, the lines tested encompassed a large number of predicted biological functions, suggesting that the activity of multiple pathways is regulated during hypoxia and each part of the response is needed for full adaptation to low oxygen.

We examined the activity of genes at 1 and 6 h of hypoxia and found that the response to hypoxia changes over time. A rapid induction of a subset of genes by 1 h of exposure was followed by more extensive changes after 1 h of exposure. A majority of genes expressed at the early time point continue to be expressed at the later time point. However, a set of genes are no longer upregulated at 6 h, suggesting that there are feedback or timing mechanisms to produce an acute response that is shut down after the initial crisis has passed as well as longer-term changes that may help the cell adapt to the loss of oxygen.

The set of genes with increased expression is diverse in function and indicative of the multiple physiological changes experienced by an organism in low-oxygen stress. Interestingly, multiple genes thought to be regulated by other stress pathways are represented. HSPs such as HSP68 and HSP23, immune-response genes such as Relish, drosocin, and IM1, heavy metal-response genes such as glutathione transferases and ferritin, Thor, a starvation response gene, and Frost, a cold-response gene, are all upregulated in hypoxia. The simplest model is that the physiological changes that take place during hypoxia activate multiple stress response pathways. For example, oxidative damage has been shown to activate NF-{kappa}B, MTF-1, Hsf, and foxo, triggering the response of the immune, heavy metal, heat shock, and nutritional stress pathways, respectively. It is possible, however, that some genes are independently regulated by the transcription factors of different stress-response pathways.

The role of oxygen in the cell is complex, as both low and high levels of oxygen pose dangers to normal function. Not surprisingly, alterations in oxygen level are carefully sensed by cellular pathways and the activity of multiple pathways is changed. The functional ramifications of such change have been difficult to determine because of the lack of such studies in genetic organisms. Here we have shown that the sweeping changes in transcript abundance, encompassing multiple genes and gene families, are functionally important during hypoxic stress.


   GRANTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
This work was supported by a Postdoctoral Fellowship from the Pacific Mountain Affiliate of the American Heart Association (no. 0325602Z to G. Liu) and a Research Scholar Grant from the American Cancer Society (no. RSG-03-154-01-DDC to E. A. Johnson).


   ACKNOWLEDGMENTS
 
We thank Michelle Black, Heidi Erickson, and Kristen Layton for help with fly stock maintenance and microarray gridding and Jason Carriere for assistance with microarray printing.


   FOOTNOTES
 
Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).

Address for reprint requests and other correspondence: E. Johnson, Institute of Molecular Biology, Univ. of Oregon, Eugene, OR 97403 (eric-johnson{at}molbio.uoregon.edu).


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 

  1. Arbeitman MN, Furlong EE, Imam F, Johnson E, Null BH, Baker BS, Krasnow MA, Scott MP, Davis RW, and White KP. Gene expression during the life cycle of Drosophila melanogaster. Science 297: 2270–2275, 2002.[Abstract/Free Full Text]
  2. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, and Sherlock G. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25: 25–29, 2000.[CrossRef][Web of Science][Medline]
  3. Bruick RK and McKnight SL. A conserved family of prolyl-4-hydroxylases that modify HIF. Science 294: 1337–1340, 2001.[Abstract/Free Full Text]
  4. Carmeliet P, Dor Y, Herbert JM, Fukumura D, Brusselmans K, Dewerchin M, Neeman M, Bono F, Abramovitch R, Maxwell P, Koch CJ, Ratcliffe P, Moons L, Jain RK, Collen D, Keshert E, and Keshet E. Role of HIF-1{alpha} in hypoxia-mediated apoptosis, cell proliferation and tumour angiogenesis. Nature 394: 485–490, 1998. [Corrigenda. Nature 395: October 1, 1998, p. 525.][CrossRef][Medline]
  5. Chen Q, Behar KL, Xu T, Fan C, and Haddad GG. Expression of Drosophila trehalose-phosphate synthase in HEK-293 cells increases hypoxia tolerance. J Biol Chem 278: 49113–49118, 2003.[Abstract/Free Full Text]
  6. Chen Q, Ma E, Behar KL, Xu T, and Haddad GG. Role of trehalose phosphate synthase in anoxia tolerance and development in Drosophila melanogaster. J Biol Chem 277: 3274–3279, 2002.[Abstract/Free Full Text]
  7. Forsythe JA, Jiang BH, Iyer NV, Agani F, Leung SW, Koos RD, and Semenza GL. Activation of vascular endothelial growth factor gene transcription by hypoxia-inducible factor 1. Mol Cell Biol 16: 4604–4613, 1996.[Abstract]
  8. Gleadle JM and Ratcliffe PJ. Induction of hypoxia-inducible factor-1, erythropoietin, vascular endothelial growth factor, and glucose transporter-1 by hypoxia: evidence against a regulatory role for Src kinase. Blood 89: 503–509, 1997.[Abstract/Free Full Text]
  9. Haddad GG and Ma E. Neuronal tolerance to O2 deprivation in Drosophila: novel approaches using genetic models. Neuroscientist 7: 538–550, 2001.[Abstract/Free Full Text]
  10. Haddad GG, Sun Y, Wyman RJ, and Xu T. Genetic basis of tolerance to O2 deprivation in Drosophila melanogaster. Proc Natl Acad Sci USA 94: 10809–10812, 1997.[Abstract/Free Full Text]
  11. Iyer NV, Kotch LE, Agani F, Leung SW, Laughner E, Wenger RH, Gassmann M, Gearhart JD, Lawler AM, Yu AY, and Semenza GL. Cellular and developmental control of O2 homeostasis by hypoxia-inducible factor 1{alpha}. Genes Dev 12: 149–162, 1998.[Abstract/Free Full Text]
  12. Kline DD, Peng YJ, Manalo DJ, Semenza GL, and Prabhakar NR. Defective carotid body function and impaired ventilatory responses to chronic hypoxia in mice partially deficient for hypoxia-inducible factor 1{alpha}. Proc Natl Acad Sci USA 99: 821–826, 2002.[Abstract/Free Full Text]
  13. Liu Y, Cox SR, Morita T, and Kourembanas S. Hypoxia regulates vascular endothelial growth factor gene expression in endothelial cells. Identification of a 5' enhancer. Circ Res 77: 638–643, 1995.[Abstract/Free Full Text]
  14. Ma E and Haddad GG. Isolation and characterization of the hypoxia-inducible factor 1ß in Drosophila melanogaster. Brain Res Mol Brain Res 73: 11–16, 1999.[Medline]
  15. Ma E, Xu T, and Haddad GG. Gene regulation by O2 deprivation: an anoxia-regulated novel gene in Drosophila melanogaster. Brain Res Mol Brain Res 63: 217–224, 1999.[Medline]
  16. Mathupala SP, Rempel A, and Pedersen PL. Glucose catabolism in cancer cells: identification and characterization of a marked activation response of the type II hexokinase gene to hypoxic conditions. J Biol Chem 276: 43407–43412, 2001.[Abstract/Free Full Text]
  17. Maxwell PH and Ratcliffe PJ. Oxygen sensors and angiogenesis. Semin Cell Dev Biol 13: 29–37, 2002.[CrossRef][Web of Science][Medline]
  18. Nambu JR, Chen W, Hu S, and Crews ST. The Drosophila melanogaster similar bHLH-PAS gene encodes a protein related to human hypoxia-inducible factor 1{alpha} and Drosophila single-minded. Gene 172: 249–254, 1996.[CrossRef][Web of Science][Medline]
  19. Semenza GL. Involvement of hypoxia-inducible factor 1 in human cancer. Intern Med 41: 79–83, 2002.[Web of Science][Medline]
  20. Semenza GL, Agani F, Feldser D, Iyer N, Kotch L, Laughner E, and Yu A. Hypoxia, HIF-1, and the pathophysiology of common human diseases. Adv Exp Med Biol 475: 123–130, 2000.[Web of Science][Medline]
  21. Shen C, Nettleton D, Jiang M, Kim SK, and Powell-Coffman JA. Roles of the HIF-1 hypoxia-inducible factor during hypoxia response in Caenorhabditis elegans. J Biol Chem 280: 20580–20588, 2005.
  22. Wang GL, Jiang BH, Rue EA, and Semenza GL. Hypoxia-inducible factor 1 is a basic-helix-loop-helix-PAS heterodimer regulated by cellular O2 tension. Proc Natl Acad Sci USA 92: 5510–5514, 1995.[Abstract/Free Full Text]
  23. Wang GL and Semenza GL. General involvement of hypoxia-inducible factor 1 in transcriptional response to hypoxia. Proc Natl Acad Sci USA 90: 4304–4308, 1993.[Abstract/Free Full Text]



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