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Renal toxicogenomic response to chronic uranyl nitrate insult in mice.

Although the nephrotoxicity of uranium has been established through numerous animal studies, relatively little is known about the effects of long-term environmental uranium exposure. Using a combination of conventional biochemical studies and serial analysis of gene expression (SAGE), we examined the renal responses to uranyl nitrate (UN) chronic exposure. Renal uranium levels were significantly increased 4 months after ingestion of uranium in drinking water. Creatinine levels in serum were slightly but significantly increased compared with those in controls. Although no further significant differences in other parameters were noted, substantial molecular changes were observed in toxicogenomic profiles. UN induced dramatic alterations in expression levels of more than 200 genes, mainly up-regulated, including oxidative-response--related genes, genes encoding for cellular metabolism, ribosomal proteins, signal transduction, and solute transporters. Seven differentially expressed transcripts were confirmed by real-time quantitative polymerase chain reaction. In addition, significantly increased peroxide levels support the implication of oxidative stress in UN toxicant response. This report highlights the potential of SAGE for the discovery of novel toxicant-induced gene expression alterations. Here, we present, for the first time, a comprehensive view of renal molecular events after uranium long-term exposure. Key words: drinking water, gene expression profiles, long-term exposure, mice, SAGE, toxicogenomics, uranyl nitrate. Environ Health Perspect 112:1628-1635 (2004). doi: 10.1289/txg.7296 available via[Online 15 October 2004]


Uranium, the heaviest of the naturally occurring elements, is widely present in the environment as a result of leaching from natural deposits, release in mill tailings, emissions from the nuclear industry, the combustion of coal and other fuels, and the use of phosphate fertilizers and weapons that contain uranium. Thus, uranium is found in various chemical forms and different levels in all soils, rocks, sea, and bedrock (Bosshard et al. 1992; Kurttio et al. 2002; Moss et al. 1983). It is also found in both food and drinking water. The wide range of levels of uranium in drinking water, together with the observation of consistently higher levels in certain community water supplies, has raised concerns regarding the potential hazard of such sources of uranium to human health.

Many isolated studies conducted on the mechanisms for the toxic effects of uranium at moderate to high acute doses on experimental animals have shown that the major health effect of uranium is chemical kidney toxicity rather than a radiation hazard (Lin et al. 1993; Miller et al. 1998, 2002). In addition only a few studies have attempted to characterize the effects of chronic exposure to uranium through drinking water (Gilman et al. 1998a, 1998b, 1998c; Kurttio et al. 2002; McDonald-Taylor et al. 1997; Zamora et al. 1998). Although chronic uranium exposure in humans has been clearly associated with increasing urinary glucose, alkaline phosphatase, and [[beta].sub.2]-microglobulin supporting proximal tubule alterations, the urinary albumin levels, which are indicators of glomerular function, are conflicting (Kurttio et al. 2002; Zamora et al. 1998). Ahhough both functional and histologic damage to the proximal tubules resulting from acute uranium exposure has been clearly demonstrated (Schramnt et al. 2002; Sun et al. 2002), little is known about the effect of long-term environmental uranium exposure in both humans and animals (Gihnan et al. 1998a, 1998b, 1998c; Kultima et al. 2002; Mao et al. 1995; McDonald-Taylor et al. 1997; Zamora et al. 1998).

Toxicogenomics is presently used to evaluate risk assessment of environmental toxicants through the identification of gene expression networks, as well as to evaluate toxicant-induced gene expression as a biomarker to assess human exposure. Several researchers are currently combining the identification of gene expression patterns representative of adverse outcomes with traditional biochemical parameter measures to categorize and classify toxic responses through direct comparison in exposed and control samples. The use of oligonucleotide-based or eDNA microarrays for understanding the biochemical processes associated with environmental chemical exposures has proven successful in recent experiments on human health risk assessment for several toxicants (Andrew et al. 2003; Bartosiewicz et al. 2001).

Because the risk assessment and establishment of exposure limits for uranium in drinking water are of" considerable importance in various areas, including Finland, we used for the first time the SAGE (serial analysis of. gene expression) approach to identify gene expression profiles associated with this hazard exposure. Because toxicogenomics provides increased confidence in extrapolation of hazards observed in animals studies to likely hazards in humans, we examined renal molecular effects of. chronic exposure to uranium in mice.

Materials and Methods


The C57BL/6J mouse was chosen because of the current state of knowledge about this transcriptome and numerous databases such as Mouse SAGE Site ( This animal model should help improve the overall quality of SAGE gene expression data. Experiments were performed with 16 male C57BL/6J mice, weighing 25-30 g (Harlan, Gannat, France) at the beginning of the study. The mice were randomly divided into three groups: one control group (group 0, six animals) and two uranyl nitrate (UN)-treated mice (groups 1 and 2, six and four animals, respectively). Exposed groups 1 and 2 received UN mineral water at concentrations of 80 or 160 mg UN/L of water, respectively, approximately 3- or 6-fold higher than levels found in bedrock of southern Finland (Juntunen I991). Uranium in water, given to control mice, was determined to be < 0.002 mg/L uranium. Body weights were measured weekly. Food intake and fluid consumption data were recorded. After 4 months of treatment all animals were euthanized by, exsanguination using cardiac puncture.

Urine and blood were collected for each group. The kidneys were either embedded in Epon for morphologic examination or snap-frozen in liquid nitrogen and then stored at -70[degrees]C until further study.

Assessment of Renal Function Parameters

Uranium contents were determined in samples of kidney using a kinetic phosphorescence analyzer (KPA; Ejnik et al. 2000). Serum creatinine and urea levels and urinary concentrations of glucose and [gamma]-glutamyl transpeptidase ([gamma]-GT) were measured by routine methods.

RNA Isolation

Total RNAs, extracted from renal tissue using the RNA isolation mini kit (Qiagen, Courtaboeuf, France), were pooled for SAGE or used individually for real-time reverse transcriptase polymerase chain reaction (RT-PCR) analyses. The amount of total RNA was determined using a fluorescent nucleic acid stain (RiboGreen RNA Quantitation Kit; Molecular Probes, Montlucon, France). The quality of the RNA was evaluated by measuring the 260:280-nm ratios and confirmed by visualization of intact 18S and 28S RNA bands after agarose gel electrophorcsis.

Analysis of Gene Expression

Production of kidney library. Kidney libraries were generated from 50 [micro]g of total RNA using the 1 SAGE kit (Invitrogen Corp., Cergy Pontoise, France) following the manufacturer's instructions (Invitrogen Corporation 2004), adapted from initial description (SAGE 2004; Velculescu et al. 1995). Because of budgetary restrictions, SAGE was performed for only control [UN(-)] and 80 mg UN/L-treated mice [UN(+)], that is, groups 0 and 1, respectively.

Tag quantification. Concatemer sequences were analyzed by using SAGE software (version 4.0; Invitrogen), which automatically detects and counts tags from sequence files. SAGE software excludes replicate ditags from the tag sequence catalog because the probability of any two tags being coupled in the same ditag is small, even for abundant transcripts. For tag identification, the tag list of each library was matched against a mouse tag database extracted by SAGE software from GenBank ( Usually, SAGE tag sequences matched more than one transcript. The average p-value computed by the SAGE software, based on a Monte Carlo analysis (Zhang et al. 1997), serves as ranking parameter to produce a list of differentially expressed genes. SAGE data for the libraries described here are available at Gene Expression Omnibus (www.ncbi.nlm.; accession nos. GSM24256 and GSM24257).

Real-Time RT-PCR

Total RNAs (1 [micro]g) from UN(-) and UN(+) renal tissue (extracted as described above) were used to generate cDNA using Moloney Murine Leukemia Virus Reverse Transcriptase (Invitrogen) according the manufacturer's conditions. Primers and probes specifically designed for selected cDNA using Primer Express software, version 2.0 (PE; Applied Biosystems, Courtaboeuf, France), are listed in Table 1. The ABI PRISM 7000 Sequence Detection System was used for detected real-time RT-PCR products with the SYBR Green I assay, according to recommendations of the manufacturer (PE; Applied Biosystems). For two cases in which we encountered difficulties with the SYBR Green I assay, we used TaqMan probe assays (Applied Biosystems) (Table 1). Each PCR reaction was optimized to ensure that a single band of the appropriate size was amplified and that no bands corresponding to genomic DNA amplification or primer-dimer pairs were present. The PCR cycling conditions were performed for all samples as follows: 50[degrees]C, 2 min for AmpErase UNG (Applied Biosystems) incubation; 95[degrees]C, 10 min for AmpliTaq Gold (Applied Biosystems) activation; and 40 cycles for the melting (95[degrees]C, 15 sec) and annealing/extension (60[degrees]C for 1 min) steps. PCR reactions for each template were done in triplicate in 96-well plates. The comparative threshold cycle ([C.sub.t]) method using Primer Express software, version 2.0, was used to determine relative quantitation of gene expression for each gene compared with the hypoxanthine guanine phosphoribosyl transferase control (listed in Table 1).

Hydrogen Peroxide Assay

To determine the impact of UN on the oxidative balance status, hydrogen peroxide levels were determined using a PeroxiDetect kit (Sigma, Lyon, France). Briefly, kidney samples from different groups (0, 1, and 2) were homogenized in the indicated phosphate buffer on ice, then centrifuged at 15,000xg for 15 min at 4[degrees]C. Supernatant samples (100 [micro]L) were incubated for 30 min with 1 mL of aqueous peroxide color reagent (aqueous solution containing 100 mM sorbitol and 125 [micro]M xylenol orange) and 10 [micro]L of ferrous ammonium sulfate reagent (25 mM ferrous ammonium sulfate in 2.5 M sulfuric acid), and the hydrogen peroxide level was measured by the absorbance at 560 nm.


General Observations

To examine the general parameters, we performed gross end-point analysis such as body and organ weight changes and histologic observations, as well as the dosage of uranium content in renal tissue and biochemical markers. No significant dose-related effects were observed on body weight gain, food intake, or water consumption. Because the concentrations of UN in the drinking water remained constant throughout the study, it is natural to assume that the measurement of UN per kilogram body weight decreased with age.

Gross pathologic examination was performed in all animals, and the histopathologic analysis did not identify any significant differences between control and exposed groups. We observed a significant dose-dependent increase in renal uranium tissue levels in groups 1 and 2 compared with control mice, using KPA. Compared with controls, there were no significant differences in kidney weights in any dose group (Table 2). Serum creatinine levels appeared to increase in dose-independent manner with UN treatment, and groups 1 and 2 showed creatinine levels significantly higher than those of controls.

Genes Responding to Toxic UN Exposure

We investigated the transcriptomic response that underlies the induction of the metal-elicited molecular modification in C57/B16J mice. SAGE was used to determine the global gene expression profile in UN toxicity. This approach allows an analysis of gene expression by the sequencing of approximately 21,000 transcripts from kidney libraries of the groups 0 and 1, which represent 5,252 and 4,069 unique tags, respectively.

We validated the quality of both libraries by comparing both with previous data on the kidney (Chabardes-Garonne et al. 2003; El-Meanawy et al. 2000; Virlon et al. 1999). For example, known markers for proximal tubules [kidney androgen-regulated protein (kap)] and thick ascending limbs [uromodulin (Umod)] were evidenced in both libraries. As expected, a large fraction of the most abundant tags matched with widely expressed mitochondrial genes or ribosomal proteins such as ribosomal proteins P1 and $26. Because the kidney mass consists predominantly of proximal tubules, a significant fraction of tags are mapped to genes known to be expressed in proximal tubular epithelial cells. Particularly, the most abundant transcripts in normal kidney were kap and glutathione peroxidase 3 (GPx3), in agreement with previous data (El-Meanawy et al. 2000).

Tags that are significantly up- or down-regulated in the UN RNA library are listed in Table 3 with their frequency and their relevant accession number. We considered only the transcripts with a significant expression change (p < 0.05). Considering the large number of sequenced tags, the number of genes expressed in kidney was evaluated by excluding tags matching mitochondrial sequences, tags with multiple matches, and nonreliable matches. Tags were arbitrarily separated in categories according to gene function. As illustrated in Table 3, most of these changes involved up-regulation. SAGE analysis revealed the expression changes of genes related to lipid metabolism [crystalline, zeta (Cryz); phosphatidic acid phosphatase type 2c (PPap2c)], carbohydrate metabolism [phosphoglycerate kinase 1 (Pgk1); sorbitol dehydrogenase 1 (Sdh1)], and amino acid metabolism (glutamate dehydrogenase (Glud); ornithine decarboxylase, structural (Odc). The UN-induced transcripts consisted mainly of genes encoding proteins associated with protein biosynthesis [ribosomal protein S25 (Rps25); $26 (Rps26); large, P1 (Rplp1); L19 (Rpl19)], protein folding [heat-shock 10 kDa protein 1 (chaperonin 1) (Hspe1)], and proteolysis [kallikrein 5 (Klk5), protein C (Proc)]. Many genes involved in signaling were upregulated, such as hormonal receptors [growth hormone receptor (Ghr), cholecystokinin A receptor (Cckar)]. Chronic exposure to UN also increased the expression of a number of genes related to oxidative process and detoxification. Among these is cytochrome P450 (Cyp4b1), which catalyzes the oxidation of a wide variety of substrates, including endogenous lipids and xenobiotics (Heng et al. 1997). Other relevant enzymes under- or over- expressed include thioredoxin, mitochondrial (Txn2); superoxide dismutase 1, soluble (Sodl); and thioether S-methyltransferase (Temt). We also mainly observed up-regulation of genes related with ion transporters including solute carrier family 34 (sodium phosphate), member 1 (Slc34a1, NaPi-II); and with electron transporters such as ATPase inhibitor, and cytochrome c oxidase, subunit IVa (Cox4a); subunit VIIIa (Cox8a); and subunit XVII assembly protein homolog (Cox 17). Finally, expression levels of several genes, in the category related to stress/apoptosis [Bcl2 associated athanogene 1 (Bag1); nerve growth factor receptor (TNFRSF16) associated protein 1 (Ngfrap1)]; immunity, (Ia-associated invariant chain (Ii)]; and translationally regulated transcripts (21 kDa) (Trt, Tpt1, Tctp, Umod) were changed.

Real-Time Quantitative PCR Analyses

To validate our SAGE data, we conducted real-time quantitative PCR analyses to verify the differential expression of seven selected genes (Figure 1). kap was chosen because of its high abundance level in the normal and contaminated kidney. Solute carrier family 34 [sodium phosphate, NaPi] member 1 (slc34a1, NaPi-II)], Sod1, Finkel-Biskis-Reilly murine sarcoma virus ubiquitously expressed (Fau), and translationally regulated transcript (Trt or Tctp) were chosen because they were increased in our data. Umod and ornithine decarboxylase structural (Odc) were chosen because their expression levels were decreased in the present study as well as in ischemic acute renal failure (ARF) or UN-induced chronic renal failure, respectively (Fleck et al. 2003). Using real-time PCR analyses, Kap, NaPi-II, Sod, Fau, and Tctp were confirmed to be significantly

increased whereas Ode and Umod were decreased in chronic exposure to UN. In summary PCR analysis confirmed the accuracy of the differences in expression levels observed in our SAGE analysis for group 1. Moreover, using real-time PCR for group 2, we observed that the expression of the selected transcripts were altered in the same direction compared with group 1, that is, increased or decreased. We noted dose-dependent increases in Tctp mRNA level at the highest concentration, and the observed decrease of Odc mRNA levels was more moderate for group 2.

Peroxide Level Measurement

To evaluate whether the variations in both Sod and Gpx transcripts may reflect a potential oxidative stress, we examined the production of [H.sub.2][O.sub.2]. The concentration of [H.sub.2][O.sub.2] in the kidney was found to be significantly higher in groups 1 and 2 compared with the control group (4.06 [+ or -] 0.06 and 4.39 [+ or -] 0.11 vs. 3.3 [+ or -] 0.02 nmol peroxide/mL) (Figure 2). Long-term UN exposure clearly caused the production of [H.sub.2][O.sub.2] levels in UN groups 1 and 2, in dose-dependent fashion.


Human exposures to metals such as uranium in both occupational and environmental settings are common occurrences. Uranium exposures are a growing concern in our society. Classically, toxicologists assess potential chronic adverse health outcomes resulting from chemical exposures by using gross end points such as body or organ weight changes and histopathologic observations. However, analysis of histologic or biochemical markers often does not provide information about the mechanisms involved in toxicant response. The study of molecular mechanisms of toxicant action might provide information crucial to the understanding of their potential adverse effects on human health. Recent technologies such as SAGE facilitate studies that add insight into the cellular response to chemical exposure. In environmental monitoring, SAGE could not only provide a method for quickly categorizing chemicals and assigning a mode of toxic action but also allow more sensitive end points to address specifically gene expression pattern.

Results reported here identify > 200 genes from approximately 21,000 tags sequenced, for which the expression in kidney changed significantly after UN long-term exposure. Most of these tags represent distinct transcripts; however, some tags, especially those detected only once, may result from PCR or sequencing errors (Velculescu et al. 1997; Zhang et al. 1997). Using classical end-point examination, including histologic appearance of the kidney and clinical and biochemical parameters, we observed that the UN doses used in this study produced only a slight alteration in serum creatinine levels and a significant but nonlinear increase of intrarenal uranium content. The dose-independent induction of the serum creatinine may be attributable, as already reported (Amin et al. 2004), to the fact that this parameter, like serum urea, traditionally used as indices of changes in glomerular filtration rate, is a relatively insensitive marker of glomerular injury. Taken together, these data suggest that the glomerular filtration rate remains relatively normal in mice after UN chronic exposure. Because the degree of renal injury appeared to be minimal in the strain of mouse used in the present study, further work will be needed to correlate the renal toxicity with the chronic uranium treatment, in dose- and time-dependent manner.

At the molecular level we observed that UN induced changes in expression profiles for oxidative response-related genes and genes encoding for ribosomal proteins, cellular metabolism, signal transduction, and solute transporters. Altered expression of these genes likely reflects an altered protein product (not determined in the present study).

Oxidative Stress Response

Reactive oxygen species (ROS) are produced by the metabolism of [O.sub.2] in all aerobic cells and are essential for normal cellular signaling functions. However, oxidative stress can occur as a result of either increased ROS generation or depressed antioxidant system, or both. Of them, SOD, catalase, and GPx constitute the main components of the antioxidant defense system. These antioxidants protect the cell against cytotoxic ROS such as superoxide anions, hydrogen peroxide, and hydroxyl radicals. The measurement of peroxides in biologic systems is one of the factors allowing the determination of the degree of certain free radicals present in specific tissues. Recently, Jung et al. (2003) suggested that [H.sub.2][O.sub.2] produced by arsenite might activate growth factor receptor by increasing its tyrosine phosphorylation. These data indicated that [H.sub.2][O.sub.2] might be a pivotal mediator of the tumor-promoting activity of arsenite (Jung 2003). In the present study we observed that UN induces dose-dependent production of [H.sub.2][O.sub.2]. We also observed an increase in Cu, Zn-SOD mRNA levels in the kidney. SOD is an enzyme responsible for dismutation of highly reactive superoxide radicals to [H.sub.2][O.sub.2]. Moreover, GPx, which scavenges [H.sub.2][O.sub.2] and lipid peroxides, had its gene expression level increased, potentially induced by the high concentrations of [H.sub.2][O.sub.2]. Induction of oxidative balance perturbation has been previously described in UN-induced ARF (Schramm et al. 2002). In addition, it has also been reported that some toxicants such as cadmium and arsenic are able to induce an increase in [H.sub.2][O.sub.2] levels after acute exposure (Ercal et al. 2001). Taken together, these data suggest that UN induces oxidative stress. Exploring this point seems of interest in evaluating the risks of UN long-term exposures.

Involvement of Genes Encoding Ion Transporters

The proximal tubule (especially the $3 segment) and the outer medullary thick ascending limb suffer the most severe injury after toxic and ischemic insult (Kwon et al. 2000; Sun et al. 2000). Although basolateral transport of sodium among the entire nephron and collecting ducts occurs via the active Na-K-ATPase pump, the active absorption is mediated by the [Na.sup.+]-dependent inorganic phosphate co-transporters (NaPi-II). In contrast to a previous study (Park et al. 1997) showing that chronic exposure to cadmium impairs the Pi transport capacity, probably by reducing the effective number of NaPi co-transporter units, we found that UN long-term exposure induces an increase of NaPi-II mRNA levels. As already suggested (Levi et al. 1994; Loghman-Adham 1997), this increase in NaPi-II is probably the result of an increase in [V.sub.max] by a transporter-shuttling mechanism, which is sensitive to disruptors of microtubule integrity. In addition, as previously reported (Moz et al. 1999) in hypophosphatemia studies, our observations suggest that UN chronic exposure could enhance the renal translational machinery. Further experiments, for example, examining the in vivo rates of NaPi-II synthesis, should allow clarification of whether UN-like hypophosphatemia affects NaPi-II translation. Moreover, Na-K-ATPase expression levels are down-regulated after UN long-term ingestion. This observation is consistent with previous work, after ischemic injury, that also shows a decreased Na-K-ATPase mRNA transcription (Kwon et al. 2000). The potential significance of this observation is that urine volume might be increased because of decreased [Na.sup.+] reabsorption. Unfortunately, urine volumes were not recorded throughout the experiments, and the monitoring of the water consumption did not reveal any change in differently treated groups compared with controls. Thus, the role of these proteins in response to UN exposure remains unclear and warrants additional investigation.

Involvement of Protein Biosynthesis-Related Genes

Interestingly, many ribosomal subunits and other factors involved in protein synthesis (elongation factor) were induced upon UN treatment. Ribosomal proteins are major component of ribosomes that catalyze protein biosynthesis in the cytoplasm of cells. Under normal growth conditions, ribosomal proteins are synthesized stoichiometrically, in relation with ribosomal RNA, to produce an equimolar supply of ribosomal components. However, regulation of the transcriptional activity of the genes encoding for ribosomal protein in differentiated human tissues appears to be less concertedly regulated than previously reported (Bortoluzzi et al. 2001). Recent progress in ribosome research provides growing evidence that ribosomal proteins can also have a function during various cellular processes such as replication, transcription, RNA processing, DNA repair, and even inflammation; all these functions are independent of their own involvement in the protein biosynthesis (Wool 1996; Yamamoto 2000). In the present work, up-regulation of transcripts for several ribosomal proteins such as RPL13a, RPL19, RPL30, RPLP1, RPS24, and RPS26 has been observed. This latter has been described as a marker to differentiate either ozone or ultraviolet B radiation environmental stresses in plants (Brosche and Strid 1999). Whereas RPS4, RPL19, and RPS18 have been involved in regulation of the development (Wool 1996), RPL13A, RPS18, and RPS24 have been associated in the maturation of mucosal epithelia (Kasai et al. 2003). Moreover, the latter was markedly decreased in colorectal cancer (Kasai et al. 2003). Taken together, these observations may suggest that UN induce a perturbation in protein synthesis and offer a new putative way of investigation on cellular proliferation study after chronic UN exposure.

Others Genes of Interest

ODC, described as the rate-limiting enzyme of polyamine biosynthesis and a marker of [G.sub.1] phase, is down-regulated in long-term UN exposure. Recently, Fleck et al. (2003) also observed a decrease in Ode expression levels 10 weeks after a single injection of UN. Kramer et al. (2001) have showed that a depletion of polyamine pool, through inhibition of ODC, causes p21-mediated [G.sub.1] cell cycle arrest, followed by development of a senescence-like phenotype and loss of cellular proliferative capacity. Thus, the decrease in Ode mRNA levels might be related to an arrest of the cell cycle after UN treatment. However, these data are inconsistent with the observed increase in protein biosynthesis-related genes. It has been previously reported that mammalian ODC protein has a very short half-life; its control is under negative feedback regulation by the polyamines, and its degradation is dependent on 26S proteasome complex (Hascilowicz et al. 2002). Interestingly, we noted an increase in proteasome subunit (Psma7) mRNA expression levels. Nevertheless, further study with added dimensions of time and doses may clarify, the observed modest Odc mRNA expression levels for the group 2 and allow a best evaluation of uranium chronic exposure impact on its expression. Of particular interest, Umod (Tamm-Horsfall protein) was decreased in the present study. This protein is one of the most abundant in the renal tubule (Bachmann et al 1990). Moreover, expression levels of UMOD have been previously reported to decrease in ischemic-induced ARF (Yoshida et al. 2002). Unexpectedly, in previous work performed in our laboratory, we showed that its expression level was increased in UN-induced ARF. in addition, an up-regulation of Umod has been observed in the progression of nephrolithiasis (Katsuma et al. 2002). However, the role of this protein remains unclear and requires additional investigation. Finally, and perhaps more interestingly, TCTP, a cytoplasmic protein usually found in both normal and tumor cell lines, is overexpressed after UN long-term ingestion. It was identified as an antiapoptotic protein (Li et al. 2001). TCTP is associated with components of the translational machinery, the elongation factors implicated in tumor formation (Cans et al. 2003). Interestingly, we observed dose-dependent increases in Tctp mRNA levels using RT-PCR analysis. Further investigations are necessary to evaluate the implication of this protein in potentially adverse health effects.

In summary, by using SAGE, we elegantly demonstrated that UN chronic exposure induces changes in expression profiles. The present report provides the first evidence that UN alters the expression of numerous genes including those encoding for oxidative-stress--related proteins, ribosomal proteins, solute transporters, and genes involved in cellular metabolism or signal transduction (Figure 3). Although these molecular changes, resulting from a subclinical toxicity, do not systematically lead to kidney failure or overt illness, our results might constitute a determining step in the identification of sensitive biomarkers to prevent the development of a UN-induced renal injury. Moreover, although studying human biology is ideal, such studies are neither feasible nor ethical. Thus, the vast majority of current biomedical research is conducted using mice and rats. However, we must keep in mind that extrapolation to humans might have some bias because humans can be exposed to many compounds simultaneously, often on a chronic or intermittent basis. Thus, the use of throughput genomic approaches after long-term exposure to mixtures of toxicants might help in the assessment of interactions such as additivity, synergism, or antagonism. The comparison of gene expression profiles could help to identify, putative new sensitive biomarkers of chronic nephrotoxicity and then evaluate the impact of environmental toxic contaminants on human health.
Table 1. SYBR Green and TaqMan primer
sequences used for RT-PCR reactions.

Gene symbol (a) Gene name (a) no. (a)

Primers using SYBR Green detection

 Hprt hypoxanthine phosphoribosyl transferase NM_013556

 Sod1 superoxide dismutase 1 XM_128337

 Odc ornithine decarboxylase, structural NM_013614

 Fau Finkel-Biskis-Reilly murine sarcoma virus NM_079900

 Tctp translationally regulated transcript NM_009429

Primers using TaqMan technology

 Hprt hypoxanthine phosphoribosyl transferase NM_013556

 Kap kidney androgen regulated protein NM_010594

 NaPi-II solute carrier family 34, member 1 NM_011392

 Umod uromodulin NM_009470

 Primer 5'[right arrow]3' Amplicon
Gene symbol (a) sequence or assay ID size (bp)

Primers using SYBR Green detection

 Hprt Forward 5'-TTGCTGACCTGCTGGATTAC-3' (b) 112




 Tctp Forward 5'-CCGGGAGATCGCGGAC-3' 92

Primers using TaqMan technology

 Hprt Mm00446968m1 (c)

 Kap Mm00495104m1

 NaPi-II Mm00441450m1

 Umod Mm00447649m1

(a) From Applied Biosystems (http://myscience.applied keyword.isp).

(b) Primer 5'[right arrow]3' sequence.

(c) Assay ID-Applied Biosystems.

Table 2. Physiologic parameters in serum and urine and uranium amount
in control group 0 and contaminated groups 1 and 2 after 4 months of
daily contamination (mean [+ or -] SE).


Parameter 0 1

Exposure (mg UN/L) 0 80
 Weight (g) 0.47 [+ or -] 0.01 0.46 [+ or -] 0.01
 Uranium amount ([micro]g/g) 0.16 [+ or -] 0.04 0.35 [+ or -] 0.02 *
 Urea (mg/dL) 59 [+ or -] 5 57 [+ or -] 5
 Creatinine (mg/dL) 0.12 [+ or -] 0.02 0.23 [+ or -] 0.02 *
 Glucose (g/L) 0.08 [+ or -] 0.03 0.08 [+ or -] 0.03
 [gamma]-GT (U/L) 86 [+ or -] 44 94 [+ or -] 42


Parameter 2

Exposure (mg UN/L) 160
 Weight (g) 0.47 [+ or -] 0.02
 Uranium amount ([micro]g/g) 1.05 [+ or -] 0.21 *
 Urea (mg/dL) 54 [+ or -] 7
 Creatinine (mg/dL) 0.25 [+ or -] 0.02 *
 Glucose (g/L) 0.04 [+ or -] 0.01
 [gamma]-GT (U/L) 119 [+ or -] 66

* p < 0.05 versus control; n = 4.

Table 3. List of tags with significant variations in expression level
induced by UN long-term ingestion (p < 0.05), their frequency, and
their relevant accession number.


Tag sequence UN(-) UN(+) Gene name (a)

 GCTGCCAGGG 11 4 Bcl2-associated athanogene 1
 GAAAGCAATG 0 6 nerve growth factor receptor
 (TNFRSF16) associated
 protein 1
 TGCCTTACTT 3 8 programmed cell death 6

Amino acid metabolism
 CGTATCTGTA 4 10 D-amino acid oxidase
 CAGTTACAAA 1 6 glutamate dehydrogenase
 TTTTACCTGC 0 8 glycine amidinotransferase
 (L-arginine: glycine
 CTACCACTGC 4 12 fumarylacetoacetate hydrolase
 ATACTAACGT 40 24 ornithine decarboxylase,
 AACAGAAAGT 1 8 phenylalanine hydroxylase

Carbohydrate metabolism
 GCAAACAAGA 11 18 isocitrate dehydrogenase 2
 (NADP+), mitochondrial
 GTGCCATATT 12 26 isocitrate dehydrogenase 2
 (NADP+), mitochondrial
 /CCAAATAAAA 17 31 lactate dehydrogenase 1,
 A chain
 TGATATGAGC 33 12 lactate dehydrogenase 2,
 B chain
 TTGTTAGTGC 70 89 malate dehydrogenase, soluble
 GCAATCTGAT 17 31 phosphoglycerate kinase 1
 GCCCAGACCT 25 41 sorbitol dehydrogenase 1
 GCTTGTGACG 1 8 transaldolase 1

Cell adhesion
 CTCTGACTTA 3 8 basigin
 GAGACTAGCA 4 10 transmembrane 4 superfamily
 member 8

Immunity and defense

 GTTCAAGTGA 4 12 la-associated invariant chain
 TATCCTGAAT 14 2 lymphocyte antigen 6 complex,
 locus A
 TTTTATGTTT 12 20 tumor necrosis factor,
 alpha-induced protein 1
 TATACATCCA 43 26 uromodulin
 TGGGTTGTCT 151 174 translationally regulated
 transcript (21 kDa)

Antioxidant and free
 radical removal
 CTATCCTCTC 297 341 glutathione peroxidase 3
 CAGCTTCGAA 12 2 glutathione S-transferase,
 theta 2
 AGAAACAAGA 7 18 superoxide dismutase 1,
 TTGCTTCTAT 20 8 thioether S-methyltransferase
 CATCAGCCTC 7 0 thioredoxin, mitochondrial

Lipid fatty acid and
 steroid metabolism
 TCTCCTTAGC 0 10 ATP-binding cassette,
 subfamily D (ALD), member 3
 TTAAGACCTG 9 18 crystallin, zeta
 TATAATAAAC 0 8 cytochrome P450, 2d9
 TGTGTGGAAT 14 20 cytochrome P450, subfamily
 IV B, polypeptide 1
 GGAGGGTGTG 4 10 phosphatidic acid phosphatase
 type 2c

Protein metabolism
 and modification

Protein folding
 CCTCCCTTTT 4 14 heat shock 10 kDa protein 1
 (chaperonin 10)

Protein biosynthesis
 GATGTGGCTG 7 22 eukaryotic translation
 elongation factor 1 beta 2
 TCACCCAATA 36 49 eukaryotic translation
 elongation factor 2
 CTAATAAAGC 18 43 Finkel-Biskis-Reilly murine
 sarcoma virus (FBR-MuSV)
 ubiquitously expressed
 (fox derived)
 TGTCATCTAG 7 14 laminin receptor 1 (67 kDa,
 ribosomal protein SA)
 TGCTGGGATG 6 16 mitochondrial ribosomal
 protein S12
 AGGTCGGGTG 7 14 ribosomal protein L13a
 TGGATCAGTC 47 66 ribosomal protein L19
 CCAGAACAGA 7 20 ribosomal protein L30
 GGCTTCGGTC 48 68 ribosomal protein, large, P1
 GTGAAACTAA 36 45 ribosomal protein S4,
 CTGGGCGTGT 3 8 ribosomal protein S15
 GTGGGCGTGT 0 6 ribosomal protein S15
 CAGAACCCAC 0 6 ribosomal protein S18
 GCCTTTATGA 4 10 ribosomal protein S24
 AACAGGTTCA 11 18 ribosomal protein S25
 TAAAGAGGCC 18 29 ribosomal protein S26

 GGTTAAATGT 1 8 cathepsin L
 CAGCAAAAAA 33 41 kallikrein 5
 GAGAGTGTGA 6 14 kidney-derived aspartic
 protease-like protein
 CAGAATGGAA 14 29 peptidase 4
 AGGCGGGATC 3 8 proteasome (prosome,
 macropain) subunit,
 alpha type 7
 CAACAAACAT 3 10 protein C
 GTAAGCAAAA 22 43 ubiquitin B

Signal transduction
 system, receptor
 TGGGACTCAC 4 14 cholecystokinin A receptor
 AGAAAAAAAA 7 14 ciliary neurotrophic factor
 TGATTTTTGT 1 10 disabled homolog 2
 GGGCAAGCCA 4 14 estrogen-related receptor,
 CATACGCATA 7 16 growth hormone receptor
 TTAAGAGGGA 12 0 transducer of ErbB-2.1


Electron transport
 GCTTTGAATG 20 35 ATPase inhibitor
 CCAGTCCTGG 12 24 ATP synthase,
 H+ transporting,
 mitochondrial FO complex,
 subunit c (subunit 9),
 isoform 1
 GTTCTTTCGT 3 8 ATP synthase,
 H+ transporting,
 mitochondrial FO complex,
 subunit c (subunit 9),
 isoform 2
 GCCGAGCATA 6 16 ATP synthase,
 H+ transporting,
 mitochondrial FO complex,
 subunit f, isoform 2
 GATAGATAAT 3 8 ATP synthase,
 H+ transporting,
 mitochondrial F1 complex,
 alpha subunit, isoform 1
 CTAATAAAAG 33 45 cytochrome c oxidase,
 subunit Iva
 TATTGGCTCT 53 74 cytochrome c oxidase,
 subunit VIIIa
 AGGGCACTGG 3 8 cytochrome c oxidase,
 subunit XVII assembly
 protein homolog
 CAGAATGTGC 3 8 NADH dehydrogenase
 (ubiquinone) 1 alpha
 subcomplex, 2
 TTATGAAATG 15 24 NADH dehydrogenase
 (ubiquinone) 1 alpha
 subcomplex, 1
 ACTGCTTTTC 1 10 NADH dehydrogenase
 (ubiquinone) 1 alpha
 subcomplex, 7

Ion transport
 TTCTAGCATA 28 10 ATPase, Na+/K+ transporting,
 beta 1 polypeptide
 CTAGGTACTG 48 91 solute carrier family 34
 (sodium phosphate),
 member 1
 ACAAATTATG 1 8 voltage-dependent anion
 channel 2

Lipid fatty acid transport
 GCTCTGATAC 0 8 sterol carrier protein 2,

 TGCTTTTACG 7 20 6-pyruvoyl-tetrahydropterin
 cofactor of hepatocyte
 nuclear factor 1 alpha
 ATTACGGTGG 7 18 aldo-keto reductase family
 1, member A4 (aldehyde
 AAGACCTATG 12 2 diazepam binding inhibitor
 CTCCTGCAGC 15 29 esterase 10
 ATCTGACTCC 3 10 hemoglobin Y, beta-like
 embryonic chain
 TAAAGCAAAA 20 43 H2B histone family, member S
 GACTTCACGC 155 182 kidney androgen-regulated
 GCACGAGCGT 7 0 low density lipoprotein
 receptor-related protein 2
 TGCTGTGACC 9 16 membrane-associated protein
 17 pending
 TGTGCTTCCC 4 12 neural precursor cell
 expressed, developmentally
 down-regulated gene 8
 TGAGCGCTGC 15 24 PDZ domain containing 1
 GGGGAGGGGG 7 0 pre B-cell leukemia
 transcription factor 2
 GGCTGGGGGC 3 10 profilin 1
 AAGTAAAGCG 6 12 SFC61, gamma subunit
 (S. cerevisiae)
 CAGCCTGAGC 4 10 selenoprotein R
 TTTCCAGGTG 1 8 selenoprotein W, muscle 1

 Accession Regulation Gene
Tag sequence no. (a) (b) symbol (a)

 GCTGCCAGGG NM_009736 - Bag1
 GAAAGCAATG NM_009750 + Ngfrap1
 TGCCTTACTT NM_011051 + Pdcd6

Amino acid metabolism
 CGTATCTGTA NM_010018 + Dao1
 CAGTTACAAA NM_008133 + Glud
 NM_025961 + Gain
 CTACCACTGC NM_010176 + Fah
 ATACTAACGT NM_013614 - Odc
 AACAGAAAGT NM_008777 + Pah

Carbohydrate metabolism
 GCAAACAAGA NM_173011 + Idh2
 GTGCCATATT NM_173011 + Idh2
 /CCAAATAAAA NM_010699 + Ldh1
 TGATATGAGC NM_008492 - Ldh2
 TTGTTAGTGC NM_008492 + Mor2
 GCAATCTGAT NM_008828 + Pgk1
 GCCCAGACCT NM_146126 + Sdh1
 GCTTGTGACG NM_011528 + Taldo1

Cell adhesion
 CTCTGACTTA NM_009768 + Bsg
 GAGACTAGCA NM_019793 + Tm4sf8

Immunity and defense

 GTTCAAGTGA NM_010545 + li
 TATCCTGAAT NM_010738 - Ly6a
 TTTTATGTTT NM_009395 + Tnfaip1
 TATACATCCA NM_009470 - Umod
 TGGGTTGTCT NM_009429 + Trt, Tpt1, Tctp

Antioxidant and free
 radical removal
 CTATCCTCTC NM_008161 + Gpx3
 CAGCTTCGAA NM_010361 - Gstt2
 AGAAACAAGA XM_l28337 + Sod1
 TTGCTTCTAT NM_009349 - Temt
 CATCAGCCTC NM_019913 - Txn2

Lipid fatty acid and
 steroid metabolism
 TCTCCTTAGC NM_008991 + Abcd3
 TTAAGACCTG NM_009968 + CryZ
 TATAATAAAC NM_080006 + Cyp2d9
 TGTGTGGAAT NM_007823 + Cyp4bl
 GGAGGGTGTG NM_015817 + Ppap2c

Protein metabolism
 and modification

Protein folding
 CCTCCCTTTT NM_008303 + Hspe1

Protein biosynthesis
 GATGTGGCTG NM_018796 + Esf1b2
 TCACCCAATA NM_007907 + Eef2
 NM_007990 + Fau
 TGTCATCTAG NM_011029 + Lamrl
 TGCTGGGATG NM_011885 + Mrps12
 TGGATCAGTC NM_009078 + Rp/19
 CCAGAACAGA NM_009078 + Rp/30
 GGCTTCGGTC NM_018853 + Rp/p1
 GTGAAACTAA NM_009094 + Rps4x
 CTGGGCGTGT NM_009091 + Rps15
 GTGGGCGTGT NM_009091 + Rps15
 CAGAACCCAC NM_138946 + Rps18
 GCCTTTATGA NM_011297 + Rps24
 AACAGGTTCA NM_024266 + Rps25
 TAAAGAGGCC NM_013765 + Rps26

 GGTTAAATGT NM_009984 + Ctsl
 CAGCAAAAAA NM_008456 + Klk5
 GAGAGTGTGA NM_008437 + Kdap
 CAGAATGGAA NM_008820 + Pep4
 AGGCGGGATC NM_011969 + Psma7
 CAACAAACAT NM_008934 + Proc
 GTAAGCAAAA NM_011664 + Ubb

Signal transduction
 system, receptor
 TGGGACTCAC NM_009827 + Cckar
 AGAAAAAAAA NM_016673 + Cntfr
 TGATTTTTGT NM_023118 + Dab2
 GGGCAAGCCA NM_007953 + Esrra
 CATACGCATA NM_010284 + Ghr
 TTAAGAGGGA NM_009427 - Tob1


Electron transport
 GCTTTGAATG NM_007512 + Atpi
 CCAGTCCTGG NM_007506 + Atp5g1

 GTTCTTTCGT NM_026468 + Atp5g2

 GCCGAGCATA NM_020582 + Atp5j2

 GATAGATAAT NM_007505 + Atp5a1

 CTAATAAAAG NM_009941 + Cox4a
 TATTGGCTCT NM_007750 + Cox8a
 AGGGCACTGG AV158262 + Cox17
 CAGAATGTGC NM_010885 + Ndufa2
 TTATGAAATG NM_019443 + Ndufal
 ACTGCTTTTC NM_023202 + Ndufa7

Ion transport
 TTCTAGCATA NM_009721 - Atp1b1
 CTAGGTACTG NM_011392 + Slc34a1
 ACAAATTATG NM_011695 + Vdac2

Lipid fatty acid transport
 GCTCTGATAC NM_138508 + Scp2

 TGCTTTTACG NM_025273 + Pcbd

 ATTACGGTGG NM_021473 + Akr1a4
 AAGACCTATG NM_007830 - Dbi
 CTCCTGCAGC NM_016903 + Es10
 ATCTGACTCC NM_008221 + Hbb
 TAAAGCAAAA NM_023422 + Histlh2bc
 GACTTCACGC NM_010594 + Kap
 GCACGAGCGT XM-130363 Lrp2
 TGCTGTGACC NM_026018 + Map17-p
 NM_008683 + Nedd8
 TGAGCGCTGC NM_021517 + Pdzk1
 GGGGAGGGGG NM_017463 - Pbx2
 GGCTGGGGGC NM_011072 + Pfn1
 AAGTAAAGCG NM_011343 + Sec61g
 CAGCCTGAGC NM_013759 + Sepr
 TTTCCAGGTG NM_009156 + Sepw1

(a) From Applied Biosystems (http://myscience.applied

(b) +, up-regulation; -, down-regulation.


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Address correspondence to M-C. Romey, Laboratoire de Genetique Moleculaire et Chromosomique, Institut de Genetique Humaine, 141, Route de la Cardonille, 34396 Montpellier Cedex 05, France. Telephone: 33 4 67 41 53 64. Fax: 33 4 67 41 53 65. E-mail:

We thank M. Claraz-Donnadieu, F. Petitot, and S. Frelon for helpful discussions.

The authors declare they have no competing financial interests.

Received 28 May 2004; accepted 14 October 2004.
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Title Annotation:Toxicogenomics
Author:Romey, Marie-Catherine
Publication:Environmental Health Perspectives
Date:Nov 15, 2004
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