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Physiol. Genomics 27: 54-64, 2006. First published June 20, 2006; doi:10.1152/physiolgenomics.00001.2006
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Received 4 January 2006; accepted in final form 12 June 2006.
Physiological Genomics 27:54-64 (2006)
1094-8341/06 $8.00 © 2006 American Physiological Society

Differential expression profiling of the blind subterranean mole rat Spalax ehrenbergi superspecies: bioprospecting for hypoxia tolerance

Aaron Avivi1, Leonid Brodsky1, Eviatar Nevo1 and Mark R. Band2

1 Institute of Evolution, University of Haifa, Haifa, Israel
2 W. M. Keck Center for Comparative and Functional Genomics, University of Illinois, Urbana, Illinois


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The blind subterranean mole rat of the Spalax ehrenbergi superspecies, living underground and exposed to fluctuating oxygen and carbon dioxide levels, is an excellent model of hypoxic tolerance. Unique structural and functional adaptations of the cardiovascular and respiratory systems allow these underground mammals to survive at severely reduced oxygen tension. Elucidation of the natural variation and evolutionary changes under hypoxia within this superspecies may have biomedical applications in ischemic syndromes and cancer. In this study, we have compared expression profiles of muscle tissue at normoxic (21%) and hypoxic (3%) levels of oxygen concentration between two allospecies of the S. ehrenbergi superspecies exhibiting differential hypoxia tolerance in accordance with their ecological regimes. Profiling was performed by cross-species hybridization using a mouse cDNA array containing 15,000 gene elements. Results uncover species-specific responses to hypoxic stress among numerous genes involved in angiogenesis, apoptosis, and oxidative stress management. Among the most striking results are differential expressions of cardiac ankyrin repeat protein (Carp), activating transcription factor 3 (Atf3), LIM and cysteine-rich domains 1 (Lmcd1), cysteine and glycine-rich protein 2 (Csrp2), and ras homolog gene family, member B (RhoB). These findings support the hypothesis that allospecies of the S. ehrenbergi superspecies are variably adapted to fluctuating oxygen tension. Differences may involve specific metabolic pathways and functional adaptations at the structural and molecular levels.

microarray; cardiac ankyrin repeat protein


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
BLIND SUBTERRANEAN MOLE RATS of the Spalax ehrenbergi superspecies are subterranean rodents that spend their entire lives in underground burrows that can be extremely hypoxic/hypercapnic (4, 5, 41, 42, 44). The Spalacidae have, over the past 40 million years, evolved physiological strategies enabling their respiratory and cardiovascular systems to cope with hypoxia more efficiently than other mammalian species (42). In field measurements, we recorded 7.2% O2 and 6.1% CO2 in burrows in flooded heavy clay soils during the Mediterranean rainy season; however, it is feasible that conditions may actually be more extreme (51).

There are four S. ehrenbergi allospecies (referred to as Spalax in this paper) in Israel, distinguished by different numbers of chromosomes and adapted to four different climatic regimes. Extreme differences in ecological conditions are observed among those places inhabited by Spalax galili (2n = 52), which inhabits the northern cool-humid Upper Galilee mountains, and Spalax judaei (2n = 60), which resides in the southern warm-dry regions in Israel. An improved hypoxic adaptation of S. galili has been established with higher normoxic breathing and heart rate (7) as well as higher hematocrit and hemoglobin levels compared with S. judaei (8). Furthermore, subcutaneous gas tension is significantly lower in S. galili than in S. judaei, implying an increased efficiency of gas extraction (6). Last, in laboratory experiments, the lowest levels of oxygen concentrations tolerated by S. galili (2.6 ± 0.4%) were significantly lower than for S. judaei (3.7 ± 0.9%) (10).

Compared with Rattus norvegicus, Spalax survives at lower O2 levels and higher CO2 for longer periods of time (9). Hypoxia tolerance mechanisms identified in Spalax compared with R. norvegicus include blood properties, anatomic and biochemical changes in respiratory organs, and differences in the structure and function of a growing list of gene products including hemoglobin, myoglobin, haptoglobin, neuroglobin, and cytoglobin (27, 30, 36, 43). Furthermore, we found varying transcription patterns of many genes and gene products related to hypoxic stress between Spalax and R. norvegicus. Factors affecting erythropoietin (Epo) and hypoxia-inducible factor1{alpha} (HIF-1{alpha}) (50, 53), as well as the expression of their receptors, differ in Spalax compared with Rattus throughout development, suggesting adaptation of Spalax to hypoxic habitats early in development (52). Capillary growth is critically dependent on various growth factors, in particular, vascular endothelial growth factor (Vegf) (55). Our previous findings demonstrate that under in vivo conditions and in an ambient atmosphere, Vegf, as well as HIF-1{alpha} (63) and HuR, a posttranscriptional stabilizer of Vegf mRNA (37), are expressed at higher levels in Spalax muscles compared with Rattus muscles (12, 13). The higher constitutive mRNA expression levels of these genes in Spalax muscle correlates with a significantly higher blood vessel concentration.

It is of note that we recently discovered that the binding domain of Spalax p53 harbors two amino acid substitutions identical to those found in human tumor cells. These substitutions result in increased activation of DNA repair elements and reduced activation of apoptotic genes by Spalax p53 compared with human wild-type p53. (11). Thus we hypothesize that the increased tolerance to low oxygen levels observed among Spalax species may be due to both increased efficiency of oxygen transport and reduced rates of apoptotic processes.

Gene expression differences between Spalax species, related to ecological and geographic variation along a north-south gradient, have shown associations to metabolic rates and brain activity under normoxic conditions (16). The goal of the present study is to probe the genetic responses of Spalax species to variable hypoxic stress. To elucidate the differential response to hypoxia in muscle between two Spalax species, S. galili and S. judaei, endemic to different ecological niches, we have used cross-species microarray experiments using a mouse cDNA array containing ~15,000 gene elements. Results uncovered species-specific responses to hypoxic stress among numerous genes involved in angiogenesis, apoptosis, and oxidative stress management. This knowledge can potentially be utilized in human gene therapy involving ischemia, stroke, and cancer and may contribute to a better understanding of physiological processes in extreme environments.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Animals and treatments.
We analyzed 12 animals, 6 representing the cool-humid northern domain (S. galili) and six representing the warm-xeric southern domain (S. judaei). Animals were captured in the field and housed in individual cages in the animal house of the Institute of Evolution at the University of Haifa. For hypoxic conditions, animals were placed in a 70 x 70 x 50 cm chamber divided into separate cells. A gas mixture of 3% O2 was delivered at 3.5 l/min for 8 h. Three individuals of S. galili and three individuals of S. judaei were treated as described above. An identical set of animals was exposed to ambient conditions (21% O2). Experiments were conducted on adults of similar weight (100–150 g). Animals were killed by injection of Ketaset CIII (Fort Dodge Animal Health, Fort Dodge, IA) at 5 mg/kg body wt. The Ethics Committee of the University of Haifa approved all animal protocols.

RNA preparations.
Total RNA was extracted using TRI reagent (Molecular Research Center, Cincinnati, OH), following the manufacturer’s instructions. RNA samples were treated with DNase I (DNA free; Ambion, Austin, TX). After extraction, all samples were stored at –80°C. RNA concentration was measured with a NanoDrop ND1000 spectrometer (NanaDrop Technologies, Wilmington, DE), and integrity was assessed on an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA).

Experimental design.
To efficiently estimate effects of hypoxia treatments, species effects, and species-by-treatment interactions independently of dye effect, we used a balanced loop design using four nodes, each representing one treatment x species combination (35). Each sample was labeled twice, once with each dye. Three replicate animals for each treatment x species combination were used. The experimental design is illustrated in Fig. 1. All data sets were submitted in MIAME-compliant format to Gene Expression Omnibus at the National Center for Biotechnology Information and can be accessed under the series accession number GSE3763.


Figure 1
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  		Fig. 1. Experimental design. A loop design with 3 biological replicates for each node (condition) was implemented. All samples were labeled twice, with Alexa 555 and Alexa 647. The head of each arrow represents labeling with Alexa 647, the tail Alexa 555.

 
Microarray design, construction, and printing.
Mouse cDNA microarrays representing 15,247 clones from the National Institute of Aging 15K libraries (NIA15K) (59), as well as positive and negative controls, were printed using an Omni Grid 100 microarray printer (Genomic Solutions, Ann Arbor, MI). In addition to the described sequences, we supplemented the array with a collection of 31 Spalax sequences incorporated in our previous studies on hypoxia. The list of these genes and accession numbers is included in Table 1.


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  		Table 1. List of Spalax sequences added to the NIA 15K mouse microarray

 
Sample labeling, hybridization, scanning, image analysis.
For all comparisons, 10 µg of Spalax muscle total RNA were reverse transcribed using an indirect aminoallyl incorporation protocol and labeled with either Alexa 555 or Alexa 647 dyes (Invitrogen, Carlsbad, CA). Slides were hybridized overnight at 42°C, washed, and scanned using an Axon GenePix 4000B microarray scanner (Molecular Devices, Union City, CA). Detailed protocols describing labeling and hybridization are listed at http://www.biotech.uiuc.edu/centers/Keck/Functional_genomics/Keck_Amino_Allyl_Labeling.doc. All slide images were analyzed using GenePix Pro 6.0 software (Molecular Devices). Analyzed slide images were manually edited, and aberrant spots were flagged for exclusion in downstream analysis.

Microarray data analysis.
The raw GenePix expression signals were preprocessed by per slide quantile normalization of Alexa 555 and Alexa 647 log2 signals (14). Herein, all signals from Alexa 555 labeling will be represented in formulas by Cy3 as will Alexa 647 by Cy5. We used the general ANOVA model for the influence of three factors on the log of the gene expression signal with a statistical threshold of P < 0.001. Specifically, our data analysis supposes that log-transformed expression signal depends on three factors: species, oxygen concentration, and dye factors. Every factor has two levels, and the model includes main effects of all three factors plus the effects of interactions between species and oxygen concentration. The formal models for data analysis are presented in the Supplemental Materials (the online version of this article contains supplemental data).

Quantitative real-time RT-PCR.
To independently confirm differential expression of Spalax cardiac ankyrin repeat protein (sCarp) and Bcl2-associated athanogene 3 (Bag3), real-time quantitative PCR was performed on an Applied Biosystems 7900 Sequence Detection System (Applied Biosystems, Foster City, CA). Primer pairs were designed using Primer Express (Applied Biosystems). All primer pairs produced a single PCR product as determined by the dissociation curve and gel analysis. PCR products were sequenced for gene identification confirmation, and similarity searches confirmed best hits to the rat orthologs of sCarp and Bag3. Primer sequences were as follows: sCarp Forward CATGACGCGGTGAGGCTGAAT, sCarp reverse TGCCAGTGCAGTACCAGATCC, Bag3 forward CGTGATACATGAGCAGAACATCAC, Bag3 reverse CTGCTGAGCTGGGTAGTGGGTCTTC, 18S forward GATCCATTGGAGGGCAAGTCT, and 18S reverse AACTGCAGCAACTTTAATATACGCTATT.

All samples were run in triplicate wells in 15-µl volumes using SYBR-Green mastermix (Eurogentec, San Diego, CA). Quantification for sCarp was based on calibration to a standard curve produced with fivefold dilutions of cDNA and normalized to the 18S control and for Bag3 calibration to a standard curve produced with twofold dilutions of cDNA and normalized to the 18S control. Two-way ANOVA was carried out using SAS 9.1 (SAS Institute, Cary, NC). All statistics were carried out using normalized sample quantities computed from the calibration curves.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
We have used a mouse cDNA microarray for cross-species analysis of the effects of hypoxia on two species of the S. ehrenbergi superspecies adapted to different climatic regions. Because of the paucity of genomic resources for these species, we used cross-species hybridization with a mouse cDNA microarray. The cross-species hybridizations of S. judaei and S. galili RNA on mouse cDNA arrays gave significant signals, comparative with those observed with mouse and rat RNA in comparable experiments. Cross-species experiments have been shown to give reliable results between species with highly similar sequences (2, 21).

Detection of differential expression profiles.
Differential expression of genes influenced either by oxygen concentration changes (hypoxic-normoxic) or by species (S. galili-S. judaei) or interactive effects of both parameters was determined. The use of a loop design allows efficient use of microarray slides while providing adequate statistical power for detection of differentially expressed genes. We used an ANOVA P value of 0.001 as the threshold for determining significant changes in expression. In consideration of the number of spots on this array, this threshold should produce an estimated 15 false positives among the genes identified as differentially expressed for each category.

Of the 15,280 spots analyzed, a total of 193 elements on the array showed significant differential expression in response to hypoxia, 380 changed across species, and 73 demonstrated an interactive effect of oxygen concentration by species. If one takes into account a redundancy rate of ~20% for the NIA15K mouse array and the fact that many elements represent sequences without annotation, these correspond to 167, 347, and 70 unique, identifiable UniGene clusters for hypoxia, species, and interaction genes, respectively. Supplemental Tables S1–S3 (see the online version of this article) list the complete set of differentially expressed genes for all the respective categories.

Particularly interesting is the list of genes showing an interaction between oxygen concentration and species, indicating the large differences in expression response to hypoxia between these two species, both exhibiting hypoxia tolerance. Among these, a number of genes with relatively large interactive changes (ratio of S. galili fold change to S. judaei fold change, generally >2 or <0.5) are presented in Table 2. It is of note that among the genes with the greatest changes of response between the two species are genes previously shown to be involved in hypoxic stress, angiogenesis, or apoptosis including sCarp, activating transcription factor 3 (Atf3), tumor necrosis factor receptor superfamily, member 12a (Tnfrsf12a), nudix (nucleoside diphosphate-linked moiety X)-type motif 4 (Nudt4), LIM and cysteine rich domain 1 (Lmcd1), syndecan 2 (Sdc2), BCL2-associated transcription factor 1 (Bclaf1), regulator of G protein signaling 2 (Rgs2), growth arrest and DNA damage-inducible 45 gamma (Gadd45g), and ras homolog gene family, member B (Rhob) (1, 18, 24, 32, 34, 48, 54, 57, 61, 64, 68).


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  		Table 2. Short list of genes with greatest interactive effects

 
PCR confirmation of microarray data.
sCarp reveals a particularly interesting expression pattern, with a 38-fold increase in response to hypoxia in S. galili; however, there is almost no change in S. judaei. To confirm this strong interaction, we carried out quantitative RT-PCR on all the samples tested with microarrays. This response was confirmed, showing an average 25-fold increase of sCarp expression within S. galili (P < 0.0001) in response to hypoxia and a nonsignificant 1.7-fold decrease for S. judaei (P > 0.1) (Fig. 2A).


Figure 2
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  		Fig. 2. Real-time quantitative PCR for Spalax cardiac ankyrin repeat protein (sCarp; A) and Bcl2-associated athanogene 3 (Bag3; B). Levels of expression are presented as relative copy no. normalized to ribosomal 18S RNA. All levels are relative to S. galili hypoxia as the base. Significant effects for both principal factors [species (P < 0.004), oxygen level (P < 0.001)] and their interaction (P < 0.0003) were observed for sCarp, whereas for Bag3, only oxygen level had a significant effect (P < 0.05).

 
Quantitative RT-PCR was also carried out to confirm microarray results for Bag3, an apoptosis inhibitor, showing a significant 1.5-fold increased expression as a result of hypoxia in the microarray data. RT-PCR results confirm this effect, with a threefold increase under hypoxic conditions (P < 0.05) (Fig. 2B).

Principal component and cluster analysis reveals major trends in variation due to effects of oxygen level and species differences.
Visualization of the sources of variation can be simplified through principal component analysis (PCA), which reduces the dimensionality of the data into a relatively small number of components. PCA of the experiment using all analyzed genes is illustrated in Fig. 3. Among the sources of variation affecting the entire set of genes on the array, a species effect independent of the oxygen level (principal component 1) explains the majority of the observed variation followed by oxygen level independent of species (principal component 2) and interaction or species-specific response to hypoxia (principal component 3). The explained variation associated with the major trends, 51, 28, and 20%, respectively, corresponds to the number of genes affected by each of the main effects and interaction.


Figure 3
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  		Fig. 3. Principal component analysis (PCA) was carried out using the gene average-normalized, estimated expression values for all genes represented on the array, using the SPSS statistical software analysis package (SPSS, Chicago, IL). Principal component 1 (PC1) represents a species effect independent of oxygen level and explains 51% of the variation; PC2 represents effect of oxygen level independent of species, explaining 28% of the variation; and PC3 represents interaction effect, explaining 20% of the variation.

 
Clustering methods aimed to classify groups of genes according to expression profiles can be used to help reveal particular patterns of expression. Figure 4A shows the overall patterns of expression for all genes showing significant responses. Within the heat map, patterns correlated with increased or decreased expression of hypoxia response genes as well as patterns indicative of differences between the two species sampled are clearly discernable. A separate cluster was produced by applying the algorithm to genes showing an interactive response (Fig. 4B). Distinct differences in response to hypoxia can be observed among the expression patterns presented for genes between the S. galili and S. judaei species. The results of quality threshold (QT) (33) clustering are presented in Fig. 5. This unsupervised method classified the total set of significant genes into 12 clusters. Visualization of these clusters aids in identification of the primary trends of expression related to the different parameters tested. Individual gene assignments to each cluster are included in Supplemental Tables S1–S3 (see the online version of this article).


Figure 4
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  		Fig. 4. A: hierarchical clustering based on significantly changing genes. Groups of genes are highlighted for higher relative expression in both species and oxygen concentrations as well as those with significant interaction. Average signal for each condition was median centered; green indicates lower expression, and red indicates higher expression compared with the median. B: profiles of genes showing strong interaction of response between 2 species.

 

Figure 5
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  		Fig. 5. Quality threshold (QT) clustering using Spearman correlation coefficient of genes showing differential expression for any parameter, species, oxygen concentration, or interaction. Shown are average profile and standard error for each cluster. Clusters represent similar trends in response to species (groups 1 and 2), increased expression in response to hypoxia (groups 3, 6, and 7), decreased expression in response to hypoxia (groups 4 and 9), and differential response to hypoxia between species (groups 5, 8, 10, 11, and 12).

 
Gene ontology and functional categories.
Gene Ontology Tree Machine (GOTM) was used to analyze and identify gene ontology (GO) categories significantly overrepresented among the genes determined to be differentially expressed. These terms were compared with categories representing the total set of genes on the array (66). Unique sets of genes, as determined by mouse UniGene categories, were created for each group of genes over- or underexpressed, depending on oxygen concentration, species, or interaction. Categories and the genes representing them are summarized in Table 3. GO categories enriched among the normoxia-hypoxia expression differences include cell differentiation, P = 0.004; programmed cell death, P = 0.002; nitric oxide signal transduction, P = 0.002; RNA splicing, P = 0.002; and blood vessel development, P = 0.0004. Categories enriched for interspecies expression differences include energy derivation by oxidation of organic compounds, P = 0.002, and positive regulation of enzyme activity, P = 0.002. The category enriched for genes showing interaction between both parameters focuses on organ development, P = 0.006.


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  		Table 3. List of GO functional categories significantly enriched above expected levels for genes represented on array

 
To enhance functional descriptions related specifically to hypoxia, we undertook literature searches for all genes showing significant differential expression due to hypoxia. These results uncover a much more comprehensive list of genes related to hypoxic stress. Table 4 lists genes detected in this experiment as responding to oxygen status that have previously been shown to be associated with hypoxia or oxidative stress in other species. Most of these genes are known to be involved in angiogenesis or apoptosis, physiological processes initiated by hypoxic stress. The functional categories determined by GO enrichment analysis and literary searches validate the significance of the microarray results focusing on the particular pathways influenced by hypoxic stress in S. galili and S. judaei.


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  		Table 4. Genes determined to be differentially expressed according to the main effect oxygen status with known functions related to hypoxia as determined by literature searches

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
The response to hypoxia has critical implications for survival and has been studied in a number of model organisms, among them rat, mouse, and zebrafish (47). Manipulation of this response has importance for biomedical aspects such as ischemia, stroke, and tumorigenesis (49). Tumor hypoxia is associated with treatment failure, enhanced metastatic potential, and poor prognosis. Analysis of tumor cells after multiple rounds of hypoxia selection show complex changes in expression patterns including upregulation of genes involved in stress resistance and anti-apoptotic signaling (62). An understanding of the physiological and molecular mechanisms allowing Spalax survival under naturally occurring hypoxic conditions may shed light on similar processes occurring in diseased states. Our aim was to elucidate transcriptional changes for two species, S. galili and S. judaei, under normoxic (21% O2) and hypoxic (3% O2) conditions. We chose to investigate neck skeletal muscle, as this tissue has large energy requirements due to the constant digging behavior of these animals.

Species-specific expression changes are related to angiogenesis and apoptosis.
The major trends in gene expression changes as a response to hypoxic conditions are illustrated by both PCA and cluster analysis, indicating groups of genes that respond to changing oxygen levels in a species-independent manner and others that respond in a species-specific manner (Figs. 3 and 5). The results of the microarray experiments point to many genes that promote angiogenesis and are affected by oxygen levels in a species-specific manner. sCarp exhibits the greatest fold change, both in the scale of response to hypoxia and regulation between species, hinting on involvement of this gene in a critical process that may define the tolerance levels of oxygen stress. Carp is a member of a conserved family of genes known as muscular ankyrin repeat proteins (39). It is highly expressed in adult cardiac and skeletal muscle and is a marker of cardiac hypertrophy (3, 67). Indeed, expression of Carp in heart-derived H9c2 cells increased their resistance to hypoxia-induced apoptosis (29). Recently, it was reported that Carp is induced in wound healing and promoted neovascularization and increased blood perfusion when an adenoviral Carp vector was implanted subcutaneously in rats (54). RhoB regulates endothelial cell survival during vascular development and has been proposed as a target for therapeutic treatment in cancer and retinopathy (1). Activation of RhoB was recently shown to stabilize HIF-{alpha} as a very early response to the presence of radical oxygen species by inhibiting ubiquitination and protein degradation and may act as a master sensor for hypoxia (56). RhoB expression is increased under hypoxia in both species; however, the change is twofold greater in S. judaei, possibly reflecting the lower tolerance and increased stress compared with S. galili. Tnfrsf12a is a transmembrane protein and primary receptor for TNF-like weak inducer of apoptosis (TWEAK), a member of the tumor necrosis factor family that induces proliferation of endothelial cells and angiogenesis (31). Expression of Tnfrsf12a increases threefold in S. galili with no change in S. judaei, lending support to the hypothesis of an increased or earlier angiogenic response in S. galili. Two genes, Csrp2 and Lmcd1, are both expressed primarily in vascular smooth muscle cells and appear to play a role in the development of the embryonic vascular system in mice (17). Both genes have been identified by two-hybrid assays as binding Gata6, a zinc finger transcription activator that mediates gene transcription controlling cell differentiation and proliferation in hematopoietic and cardiovascular tissues (48). Lmcd1 forms a complex that blocks DNA binding by Gata6, whereas complexes formed with Csrp2 appear to enhance binding and promote transcription. Although these genes appear to have opposite effects, the interaction of GATA6 with these gene products is most likely dependent on colocalization within the cell. GATA6 may interact with both coactivators and corepressors to finely regulate vascular smooth muscle gene transcription. Both Lmcd1 and Csrp1 show increased expression in S. galili muscle exposed to hypoxic conditions. Although angiogenesis appears to be a common response to hypoxic stress in both species, the strong interactive response of many genes suggests differences in the scale or efficiency of particular pathways involved in vascularization between these closely related species that have adapted to environments with different severities of hypoxia. Induction of Carp and other gene products enhancing angiogenic processes may aid in maintenance of the dense vasculature that allows tolerance to low oxygen levels observed for S. galili.

Additional elements affected by hypoxia that show strong differences of response between species include regulator of G-protein signaling 2 (Rgs2), which responds to oxidative stress and heat shock (68); Bcl2-associated transcription factor 1 (Bclaf1); activating transcription factor 3 (Atf3); and growth arrest and DNA damage-inducible 45 gamma (Gadd45g). Bclaf1, also known as Btf, is highly expressed in skeletal muscle, and when overexpressed induces cell death by a mechanism involving the inhibition of anti-apoptotic bcl-2 family proteins (32). We show evidence of increased expression of Bclaf1, which would contradict the original hypothesis of reduced apoptosis; however, as shown below, there is evidence of other anti-apoptotic or stabilizing factors that are also increasing under hypoxia. Atf3 is a leucine zipper transcription factor that is induced by a wide range of stresses, including genotoxic and nutritional stress, and is involved in cell proliferation, apoptosis, and invasion (28, 58). Atf3 interaction with p53 prevents ubiquitination and thus stabilizes the p53 protein. S. ehrenbergi p53 was previously shown to induce DNA repair mechanisms over apoptosis; thus higher levels of S. ehrenbergi Atf3 induced by hypoxic stress probably contribute to cell survival rather than cell death. Interestingly, both Atf3 and Vegf RNA levels are subject to a common regulator, the RNA binding protein HuR. Binding of HuR to Atf3 and Vegf mRNA results in stabilization and subsequently an increase in the half-lives of these mRNA species (46). Although we do not present data confirming differences in HuR expression, other regulatory mechanisms, such as translation or protein modifications, may be responsible for differences resulting in differential expression of Atf3. Atf3 is highly upregulated in S. galili, possibly conferring a protective effect by stabilizing p53 and DNA repair. Additionally, Gadd45g, which is induced by DNA damage and a promoter of apoptosis in cancer cells (65), is upregulated to a greater degree in S. judaei (or partially suppressed in S. galili) under hypoxic conditions.

Evidence for a protective response through inhibition of apoptosis under hypoxic stress is also supported by an increase in Bcl2-associated athanogene 3 (Bag3) in both species under hypoxia, as shown by both microarray and real-time PCR results. Higher levels of Bag3 expression are associated with increased survival of neoplastic leukocytes (15) and inhibition of apoptosis and may protect transformed cells through inhibition of protein degradation. Bag3 binds heat shock protein 70, inhibiting protein degradation, thus resulting in retained function of poly-ubiquitinated proteins and enhanced cell survival (22). These data suggest a complex response at high levels of stress by cell survival through DNA repair mechanisms, a balance of anti- and pro-apoptotic factors, and enhanced blood perfusion through development of new blood vessels.

Splicing and RNA binding factors are induced as a result of hypoxic stress.
Functional categories of differentially expressed genes were compared using GO terms with enrichment analysis (23). One of the important processes induced by hypoxia identified through GO analysis is RNA binding and splicing. As seen from Table 4, a relatively large number of genes described as splice factors or RNA binding motifs are induced in muscle of both species under severe hypoxia. There is growing evidence that changes in the levels of splicing factors modulate splicing patterns and thus may be working as genetic modifiers (45). This mechanism, affecting ratios of splice variants, is known to affect severity of disease and may contribute to the modification of complex traits as well as apoptosis. Proteins with serine-arginine-rich domains (SR proteins) bind to enhancers and silencers, changing the recognition of splice sites (26). Thus alternate exons can be regulated by changing concentrations of SR proteins (38). As a reaction to stroke, neuronal ischemia was shown to induce changes in the intracellular location of the splicing regulatory protein tra-ß1, which interacts with components of the splicing complex including Sfrs2 and Sfrs6. Induction of ischemia stimulated transcription of an alternate form of ICH-1 (Caspase 2) from a form that promotes apoptosis to a form that prevents apoptosis (20). Chromosomal translocations resulting in fusion proteins involving a splice factor, Sfpq, are associated with renal cell carcinoma (19). Additional examples of alternate splicing affecting disease state and apoptosis are reviewed in Ref. 25. These serine-arginine-rich splicing factors and others are induced in S. ehrenbergi muscle in response to hypoxia (Table 4). Thus changes in ratios of splice variants for genes affecting apoptosis may be an adaptive protective response to potential cellular damage as a result of low oxygen levels. Additionally, the frequencies of Vegf splice variants vary under hypoxic stress (60). It has been documented that particular splice variants of Vegf (Vegf165) can bind to the cell surface and extracellular matrix-associated heparan-sulfate proteoglycans and can release angiogenic factors such as bFgf, which may have a synergistic effect with Vegf, enhancing angiogenesis (40). Our present findings also indicate differential expression of syndecan 2 (Sdc2), also known as heparin-sulfate proteoglycan 1 (Hspg1). Sdc2, a transmembrane protein, functions synergistically with Vegf and is required for sprouting angiogenesis in zebrafish and mouse (24). Our results show that, although many genes involved in angiogenesis show increased expression, Vegf is downregulated by a factor of two under hypoxic conditions in both species. This is concurrent with previous work comparing Vegf levels in S. judaei at 6% oxygen (13). This may reflect the behavior of a particular splice variant; however, to confirm this, additional variants of Vegf need to be cloned from the S. ehrenbergi superspecies. The Atf3 transcript is known to undergo alternative splicing with changing ratios of splice variants regulated by amino acid availability under nutritional stress (46). Differing Atf3 protein lengths were shown to repress or activate transcription of target genes. Evidence from changing levels of these genes and increased levels of multiple splice factors hints that alternate splicing induced by hypoxic stress may play a critical role in the survival of these species.

Increased metabolic rate of S. galili is reflected in expression differences between species.
S. galili has an increased normoxic breathing and heart rate with higher oxygen consumption compared with S. judaei (7). Differentially expressed genes between species include an enrichment of genes involved in energy derivation by oxidation of organic compounds (Table 3). Many of these genes are involved in glycolysis and the citric cycle. Most of the genes identified in this category have increased expression in S. galili, possibly reflecting the increased rate of respiration observed under normal conditions.

In summary, it is important to recognize that only two levels of oxygen were considered here, representing the extreme tolerance levels (21 and 3%), with sampling taken at a single time point (8 h). From the data observed, we show support for larger expression changes among genes that enhance blood vessel formation in S. galili compared with S. judaei, explaining the difference of minimum oxygen concentrations tolerated. With respect to apoptotic processes, the data appear to be more complex, showing both known pro- and anti-apoptotic factors changing in both species. As has been demonstrated in other experiments, alternate splicing may be a major factor that could contribute to an explanation of the observed contradictions; however, the paucity of sequence data prevents further exploration of this hypothesis. A more comprehensive understanding of the differences in response between the two species would require time course experiments at different levels of oxygen concentration. In addition, we should also consider the possibility of alternate functions for Spalax orthologs of mouse or rat genes, as observed for differences of p53 function between Rattus and Spalax.

The present experiment identified genes differentially expressed in response to hypoxic conditions and, more importantly, differentially responding to hypoxic stress between the two hypoxia-tolerant species, S. galili and S. judaei. Many of these genes, such as RhoB, Bag3, and Carp, have been targeted as candidates for intervention in cancer therapeutics through regulation of angiogenesis or apoptosis (1, 22, 29). These data may lead to a greater understanding of how individual species cope with particular environmental stresses and the pathways critical for survival. The ability of allospecies of the S. ehrenbergi superspecies to cope with sharp fluctuations in oxygen and carbon dioxide concentrations provides an ideal model for bioprospecting of genes and control elements that may have important implications for biomedical aspects of ischemia and cancer.


   ACKNOWLEDGMENTS
 
We thank Alla Fishman for reviewing the manuscript, Al Bari (University of Illinois) and Alma Joel (Haifa University) for technical assistance, and two anonymous reviewers for critical comments.

This work was funded by the W. M. Keck Center for Comparative and Functional Genomics, University of Illinois, and the Ancell-Teicher Research Foundation for Genetics and Molecular Evolution.


   FOOTNOTES
 
Address for reprint requests and other correspondence: M. Band, Univ. of Illinois, 1201 W. Gregory Dr., Urbana, IL 61801 (e-mail: markband{at}uiuc.edu); or A. Avivi, Institute of Evolution, Univ. of Haifa, Haifa, Israel 31905 (e-mail: aaron{at}research.haifa.ac.il).

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


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
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