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1 Nestlé Research Center, CH-1000 Lausanne 26
2 Center for Integrative Genomics, Université de Lausanne, CH-1015 Lausanne
3 Swiss Institute for Experimental Cancer Research, 1066 Epalinges s/Lausanne, Switzerland
4 Nestle Purina Pet Care, St. Louis, Missouri 63164
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIAL AND METHODSRESULTSDISCUSSIONREFERENCES |
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B, zinc binding protein factor (ZBPF), GC-box factors SP1/GC (SP1F), and early growth response factor (EGRF) transcription binding motifs. The cellular location of another of the differentially expressed ABC transporters, Abcc3, was examined by immunohistochemistry. Staining revealed that the protein is consistently expressed in the basolateral compartment of enterocytes along the anterior-posterior axis of the intestine. Furthermore, the intensity of the staining pattern is concordant with the expression profile. This agrees with previous findings in which the mRNA, protein, and transport function of Abcc3 were increased in the rat distal intestine. These data reveal regional differences in gene expression profiles along the intestinal tract and demonstrate that a complete understanding of intestinal ABC transporter function can only be achieved by examining the physiologically distinct regions of the gut. ATP-binding cassette transporters; microarray; intestine; anterior-posterior axis
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIAL AND METHODSRESULTSDISCUSSIONREFERENCES |
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ABC transporters are multispan membrane proteins that are involved in the directional transport of a wide variety of substrates, including sugars, amino acids, glycans, sterols, phospholipids, peptides, proteins, toxins, antibiotics, and xenobiotics across biological membranes (11). Family members have been identified and grouped based on conserved sequence motifs within their ATP-binding domains (also referred to as nucleotide binding domains), which lie between the characteristic Walker A and B motifs (31). Based on structural similarities and the sequence homology of these nucleotide-binding domains, the ABC superfamily has been further subdivided into seven subfamilies, ABCA to ABCG (7). Furthermore, ABCs are highly conserved between species, reinforcing their functional importance in the transport of molecular compounds. A thorough review by Dean (6) was recently published and described the structure, molecular organization both within and between species, and the known functions of ABC transporters and how they may contribute to the onset of disease. Within this review (6), ABC family homology was compared and contrasted between the mouse and human. To date, 49 ABC family members have been identified in the mouse, and most of these show high concordance with their corresponding human ortholog. The differences consist of: 1) an additional ABCG subfamily member in the mouse (Abcg3), 2) duplication of ABCB1 and ABCA8 in the mouse (Abcb1a/b and Abca8a/b, respectively), and 3) loss of Abca10 and Abcc12. Additionally, a cluster of three murine ABCA subfamily members has been identified in the mouse genome, but these have not been assigned human orthologs because of the incomplete characterization of this region of the human genome (6).
As a first step in elucidating their functions in eukaryotes, it is critical to ascertain where in the body these transporters are expressed. A recently published study by Langmann and colleagues (17) described a whole body gene transcript characterization of all currently known human ABC transporters using real-time PCR (RT-PCR). The authors analyzed and revealed the expression profiles of these genes in 20 different tissues and concluded that tissues involved in secretory function (adrenal gland), metabolic function (liver), barrier function (small intestine), and development (uterus, testis) had high levels of ABC transporter transcripts. The authors did not subdivide the small intestine into its functionally different sections: duodenum, jejunum, and ileum. These various sections have been previously shown to have different rates for the transport-mediated uptake of orally delivered compounds in the rat intestine (21, 27). Furthermore, the bioavailability of both medicinal and nutritional compounds is dependent on the intestinal environment, where factors such as disease, pH, motility, and microflora can vary along the intestinal tract (9). As ABC transporters are highly involved in the transport of nutrients and drug compounds alike, we propose that expression patterns are a prerequisite to deciphering their functions in the gastrointestinal tract (GIT). The mouse was used to generate statistically significant and biologically relevant information for this family of genes because of the high degree of homology and conservation of ABC transporters between eukaryotes and their potential to generate specific knockout models for further analysis.
Recently, Bates and colleagues (1) conducted a study examining the global differential gene expression along the anterior-posterior (A-P) axis of the adult mouse GIT. The authors used the mouse GEM1 cDNA microarray from Incyte Genomics, which contains 
8,000 sequence-verified expression sequence tags (ESTs), to identify novel genes and functional relationships in the GIT (1). Several ABC transporters (16 of 49) could be identified in their data set and indicated that some of these genes are differentially expressed along the intestinal tract; however, the majority of ABC transporters are either not annotated or not present on the mouse GEM1 array.
A more complete picture of murine intestinal mRNA expression patterns is obtained using high-density oligonucleotide microarray technology. The present work extracts all ABC transporters currently annotated and identifiable in the MuU74v2 GeneChip set (43 of 49 transporters currently annotated) for a focused discussion on this important molecular family. Despite both the differences in mouse strains (Hsd:ICR vs. C57BL/6) and array technology (Affymetrix vs. cDNA) used in this study vs. the Bates study (1), concordance was high for the 16 ABC transporters found in common, reinforcing the highly conserved nature of this transporter family. Our findings indicate that 8 of the 43 ABC transporters examined are differentially regulated along the murine intestinal tract. Furthermore, examining the promoter regions and the cellular location of differentially expressed ABC transporters revealed complementary information required for elucidating the functions of these transporters in the intestinal tract.
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MATERIAL AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIAL AND METHODSRESULTSDISCUSSIONREFERENCES |
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Nucleic acid preparation.
Total RNA extracts were provided by AMS Biotechnology (Lugano, Switzerland), and RNA extraction was performed identically for each pool of mice. Within a pool, the duodenum, jejunum, ileum, and colon were harvested from each animal, pooled, and homogenized, and the RNA was extracted by a modified guanidium thiocyanate method (RNWAY Laboratories, Seoul, Korea) as previously described (28). Although pooling mRNA samples is commonly performed because of low quantities of mRNA and/or cost restrictions, recent evidence indicates that pooling RNA also provides equivalent statistical power compared with individual analyses (13, 24). To ascertain the condition of the RNA pools, RNA quality was tested by formaldehyde gel electrophoresis and was stored and transported on dry ice in an ethanol suspension containing 0.1 M sodium acetate. RNA was then repurified, according to manufacturer’s instructions, using the Nucleospin kit, and contaminating genomic DNA was removed with by DNase I treatment (Macherey-Nagel, Oensingen, Switzerland). All the samples were monitored by agarose gel and with the Agilent 2100 Bioanalyser (Agilent Biotechnologies, Germany) and consistently demonstrated high-quality RNA (28S/18S ratio approximately 2, but always less than 3).
cRNA preparation.
For each gut tissue section, 5 µg total RNA was used as the starting material for all individual samples. cRNA was prepared as previously described for all experimental samples except two (R. Mansourian, unpublished observation). Because of low yields in cRNA synthesis with two of the three jejunum samples, it was necessary to pool the cRNA from multiple synthesis steps. Corresponding data analysis [i.e., counting the number of outliers identified using both the global error assessment (GEA) model and the rudimentary 2- and 3-fold cutoff rules] indicated that this did not have any significant effects on the variability in gene expression measurements between jejunum samples compared with the other intestinal regions (data not shown).
Array hybridization and scanning.
Samples were hybridized to the Affymetrix MuU74v2 set (Affymetrix, High Wycombe, UK), which consists of three GeneChips (A, B, and C) containing 33,000 unique genetic elements. For all experimental replicates, the same cRNA sample was hybridized to each of the three GeneChips. No detrimental effects on the quality of cRNA were observed after three hybridizations, as determined by comparing the variability in intensity signals to the intensity signals of all genes present on each GeneChip (data not shown). Scanning was performed as previously described (23). Readings from quantitative scanning were analyzed with Affymetrix Gene Expression Analysis Software (MAS 5.0). The complete data set is publicly available in the NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) through the accession number GSE849.
Data analysis.
Differential gene selection was determined using two statistical approaches: 1) a classic ANOVA and 2) a GEA method of analysis. ABC genes considered differentially regulated along the intestinal tract were statistically significant (
0.01) by both the classic ANOVA and the GEA model.
The GEA approach takes advantages of several inherent characteristics of microarrays that result in an increased statistical power for the data analyst. When examining genomic data sets, most genes are found to be stably expressed across all conditions (14, 23). Therefore, rather than treating each gene on the microarray as a unique and unrelated element, neighboring genes are binned into groups of 200 based on similar intensity signals, and the mean squared error is calculated for each bin. The binning of genes greatly increases the statistical power of the GEA approach and yields results that are statistically significant and highly concordant with an alternate gene expression analytical platform (i.e., RT-PCR). For a detailed description and general protocol of the GEA model, we encourage readers to contact us.
Real-time polymerase chain reaction.
All mouse primer and probe sets were synthesized by Applied Biosystems (Foster City, CA) through their Assays on Demand (AoD) and Assays by Design (AbD) services. For those primer/probe sets created using the AbD service, complete sequences were obtained from the Ensembl database (http://www.ensembl.org/), and target sequences were selected over exon splicing sites to minimize any potential signal stemming from contaminating genomic DNA (Table 1). AbD and AoD primer/probe solutions were received at a premixed, ready-to-use concentration of 18 µM for each primer and 5 µM for the probe.
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= 0.01) was used to confirm differences in gene expression in pair-wise analysis (i.e., all four intestinal sections compared).
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0.05 using a Student’s t-test.
Promoter analysis.
Genes with expression profiles highly correlated (r = 0.90–0.99) with one of the eight differentially expressed ABC transporters were selected for promoter analysis. The putative human homolog corresponding to each gene was identified according to the Ensembl annotation. Using the publicly available promoter analysis tools Chip2Promoter, MatInspector, and FrameWorker by Genomatix (http://www.genomatix.de), known or putative promoter regions were identified and checked for both single promoter elements (MatInspector) and complex models (FrameWorker) reflecting both the promoter element composition and the functional organization of individual elements (15, 29). In all circumstances, promoter regions were defined by Genomatix software as the 500 base pairs (bp) upstream and the 100 bp downstream of the predicted transcript start site. Complex models were identified by the FastM method (15), which combines a search algorithm for individual transcription factor binding sites with a distance correlation. Only single elements or complex models were selected if they were common to both the murine and human sequence, as sequence conservation in noncoding, upstream regions of orthologous genes from man and mouse is likely to reflect common regulatory DNA sites (8). The distance between elements was required to be in the range of 10 to 100 base pairs. All remaining parameters used Genomatix defaults.
Immunohistochemistry.
Serial tissue sections of 5 µm were obtained using a cryostat (model HM 500 OM; Microm Laborgeräte, Walldorf, Germany), air dried, and fixed in acetone for 10 min. Slides were air dried and placed in 1x PBS until use. All future rinses were performed using 1x PBS. Endogenous peroxidase was blocked with 0.3% H2O2 (Merck Eurolab, Switzerland) and rinsed for 5 min. Biotin and avidin blocking was performed according to manufacturer’s instructions (DAKO, Carpinteria, CA). Slides were then blocked with 10% normal rabbit serum (Sigma, Buchs, Switzerland). Abcc3 protein was detected by incubating 1 µg/ml goat anti-mouse Abcc3 antibody (Santa Cruz, Heidelberg, Germany) in 10% normal rabbit serum for 1 h at room temperature, which was then rinsed with gentle agitation. Biotin-conjugated rabbit anti-goat antibody (Zymed Laboratories, S. San Francisco, CA) was then incubated at 2 µg/ml in 10% normal rabbit serum for 1 h at room temperature. After rinsing with gentle agitation, slides were treated with the TSA fluorescence system (PerkinElmer, Boston, MA) according to the manufacturer’s instructions. Controls included omission of the primary antibody or inclusion of an isotype control antibody (goat anti-mouse IgG, Santa Cruz).
Tissues were mounted with fluorescent mounting medium (DAKO), sealed, and stored at 4°C in the dark. All images were obtained using a Hamamatsu camera (Hamamatsu Photonics) and a Zeiss Axioplan II microscope (Zeiss, Feldbach, Switzerland).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIAL AND METHODSRESULTSDISCUSSIONREFERENCES |
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Differential gene expression was determined primarily using the GEA method, as classic statistical methods (ANOVA, Student’s t-test) often do not prove to be robust using three replicates (R. Mansourian, unpublished observation). It has previously been demonstrated that the GEA approach can accurately identify differentially expressed genes at both low and high numbers of replication. To reinforce this point, GEA selected seven additional transporters (Abca2, Abca7, Abcb1a, Abcb4, Abcb10, Abcg1, and Abcg2) as differentially expressed in the gut, whereas the classic ANOVA attributed much less significance to these results (Table 2).
The natural logarithmic values of normalized expression results for all ABC transporters are listed in Table 2. It is interesting to note that, at the mRNA level, most of the ABC transporters are not differentially expressed along the intestinal tract. Indeed, only eight transporters were identified as differentially expressed in the gut by both the classic ANOVA and GEA ( < 0.01 for both statistical tests). Differentially expressed transporters were Abcb2, Abcb3, Abcb9, Abcc3, Abcc6, Abcd1, Abcg5, and Abcg8. When visualizing all ABC transporters on a bivariate plot comparing the small intestine (duodenum, jejunum, and ileum values averaged to obtain a single value) to the colon, where the mean of the natural logarithm of the fold change (M) is plotted against the mean expression value (A), one can immediately observe that the great majority of these transporters (identified by green dots) lie within the data cloud (Fig. 1). Additionally, estimation of a Lowess (also known as "Loess") regression function predicting the local mean standard deviation demonstrates that the majority of these transporters are not differentially expressed. Furthermore, as the x-axis is representative of absolute expression levels, it is clear that ABC transporters are present in the intestinal tract at various levels, from lowly or not at all expressed up to highly expressed. The aforementioned eight differentially expressed ABC transporters are indicated and place their degree of differential expression in context with all genetic elements present on the GeneChips.
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< 0.01), even in circumstances where a fold change of 4.7 (Abcc6 in the jejunum) is seen. In contrast, RT-PCR was able to identify additional statistically significant differences in situations where the microarray was not, such as the 3.8-fold change observed for Abcc6 in the jejunum. Findings such as these were expected because of the inherent differences in sensitivities between the two methods (33). Indeed, identifying 100% of the truly differentially regulated genes in a microarray experiment is still complicated by lowly expressed genes (i.e., corresponding to many transcription factors and receptors), which may be highly variable within and/or between biological treatments (19). The development of robust statistical methods, such as GEA, aim to dissociate those lowly expressed genes that are variable within a treatment, i.e., technical variability, from those that are variable between experimental conditions, i.e., biological variability (R. Mansourian, unpublished observation; 19). As demonstrated in the current study, GEA methodology proved to have increased sensitivity compared with the classic ANOVA for gene selection. Whereas GEA identified Abcb1a and Abcd1 as differentially expressed, the classic ANOVA failed to assign statistical significance to the changes in expression (Table 2). RT-PCR confirmed that these genes were indeed differentially expressed in the gut, reinforcing the improved sensitivity of the GEA method for the detection of low-abundance genes. Finally, in agreement with the decreased sensitivity of microarrays, the results demonstrate that microarray platforms tend to underestimate the relative changes in mRNA expression between samples (33).
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The cDNA data set contained expression information for 16 of the 49 ABC transporters. Those ABC transporters found in common between the two data sets are identified with an asterisk in Table 2. Of the eight ABC transporters identified in our data set as differentially regulated along the gut, only two were present in the cDNA data set: Abcd1 and Abcg5. Figure 2 demonstrates that despite the experimental differences, both cDNA and Affymetrix platforms indicate that Abcg5 is expressed at significantly lower levels in the colon and similarly expressed in the duodenum, jejunum, and ileum. This finding is in agreement with RT-PCR data (Table 3). Expression-profiling trends revealed that Abcd1 is most highly expressed in the jejunum and most lowly expressed in the colon (Fig. 2), as confirmed by RT-PCR. The remaining 14 ABC transporters found in the cDNA data set were not differentially expressed along the intestinal tract. This agrees with our high-density oligonucleotide results and further specifies that the members of this family are expressed at various levels in the intestine and that most of these transporters are not differentially expressed.
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B (NFKB; 0.57) and the NKX/DLX-homeodomain site (NKXH; 0.67). Other single elements were found in common, such as EGR/nerve growth factor-induced protein C (EGRF) and GC-box factors SP1/GC (SP1F), but their individual FW scores were below 0.5. However, transcription factors often associate into complexes to correctly activate the transcription of a given gene; therefore, those single elements that have an FW score below 0.5 may be found in complex models with significant scores. Indeed, we find that NFB, ZBPF, SP1F, and EGRF associate to form a complex model with FW scores of 0.24/1.0, as illustrated in Fig. 4. Although additional complex models exist, this model consisted of the greatest number of single elements (i.e., 4) with the highest FW scores. Furthermore, the importance of Sp1 binding sites in both Abcb9 and fibulin-1 have been experimentally demonstrated by Castoldi and Chu (4) and Kobayashi et al. (16), respectively.
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Abcc3 protein distribution along the intestinal tract.
Abcc3 (MRP3) was selected for further analysis at the protein level because it was one of the eight differentially expressed ABC transporters. Immunohistochemical staining for Abcc3 revealed a similar cellular pattern of expression along the intestinal tract (Fig. 5). Protein location is restricted to the villi of the intestine, as no staining was present in the crypts of Lieberkühn (data not shown). Furthermore, staining appeared to increase in intensity from crypt to villi, suggesting that Abcc3 protein is predominantly expressed in fully differentiated enterocytes. In all segments of the intestine, Abcc3 is expressed basolaterally in enterocytes (Fig. 5, A–D). Abcc3 is most highly expressed in the colon and to a lesser extent in the various regions of the small intestine. Although not quantitative, the high degree of protein staining in the colon visually concords with the mRNA expression profile, which also indicated a higher level of Abcc3 transcript in the colon. This qualitative statement is based on the lower exposure time required to capture protein staining in the colon (0.48 s) compared with the small intestine (between 1.04 and 1.44 s).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIAL AND METHODSRESULTSDISCUSSIONREFERENCES |
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Few studies have examined the expression profiles of ABC transporters in the intestine to elucidate their region-specific functions. Studies by Rost et al. (26) and Chianale et al. (5) demonstrate the importance of treating the small intestine as functionally distinct regions rather than as a single entity. For example, Rost and colleagues (26) found that Abcc3 (MRP3) was predominantly expressed (mRNA and protein) in the ileum and colon of the rat intestine, and Chianale et al. (5) found that Abcb1a (corresponding to ABCB4 in the human) mRNA, protein, and transport rate were all approximately sixfold higher in the mouse ileum vs. the duodenum. Because of the high degree of homology for ABC transporters between eukaryotes, similar findings in humans would be expected. A good example supporting homology between species was demonstrated by Stephens et al. (30), in which the authors found that P-glycoprotein (human ABCB1)-mediated drug efflux increased along the rat and human intestine in a similar manner. Taken together, these examples demonstrate the importance of distinguishing between the various regions of the small intestine, and, furthermore, indicate that differences in mRNA levels can be indicative of functional differences across eukaryotes.
Approximately half of the 48 human ABC transporters have been characterized to various extents, with the remaining having currently unknown functions; therefore, interpreting the intestinal profiles of all differentially expressed ABC transporters is not possible at this time. Of noticeable interest are the overall low expression levels of ABC transporters in the gut. The association of these proteins in the transport of a multitude of nutritional and chemical compounds would imply that they might be highly expressed. This result may be explained in several ways. First, the functions/actions of many of the ABC transporters may stem from posttranscriptional regulation, i.e., low mRNA levels but a high degree of protein synthesis and/or stability. Second, ABC transporters may have highly sensitive promoter elements that permit a rapid response (i.e., increased transcription) when exposed to a specific substrate. Alternatively, this result may arise as a result of the experimental design rather than a biological phenomenon. The use of intestinal tissue rather than a specific intestinal cell type (e.g., absorptive cells) may have diluted their highly localized expression patterns.
Of those ABC transporters identified as differentially expressed in the gut, Abcb9, Abcc6, and Abcd1 have not been previously examined in the intestine, and their functions in this organ are currently unknown. Nevertheless, current information concerning their functions permits some speculation regarding their expression profiles in the intestine. For example, Abcb9 ("transporter associated with antigen processing-like," or TAPL) is closely related to the TAP2 gene and has a intestinal expression pattern similar to the TAP1/TAP2 complex (described in more detail below). This lysosomal protein may play a role in the translocation of peptides from the cytosol into the lysosome for degradation (16, 34). Abcc6 is a confirmed member of the MRP family of drug efflux pumps and has been demonstrated to transport glutathione conjugates, thereby having a potential role in the regulation of xenobiotic bioavailability in the intestine (2, 6). Finally, Abcd1 is a peroxisomal half transporter that is mutated in adrenoleukodystrophy, which is characterized by a reduced peroxisomal very-long-chain fatty acid (VLCFA) ß-oxidation (6). As the primary site for dietary fatty acid absorption occurs in the upper intestine, the higher Abcd1 expression levels in the duodenum and jejunum suggest that this peroxisomal transporter is actively involved in the metabolism of dietary VLCFA. Although the definitive functions of intestinal Abcb9, Abcc6, and Abcd1 have yet to be ascribed, two pairs of half transporters, Abcb2/Abcb3 (TAP1/TAP2) and Abcg5/Abcg8, have previously been studied in the intestine and have been implicated in immune responses and sterol transport, respectively.
TAP1 and TAP2 ("transporters associated with antigen presentation/processing") have been found to preferentially transport 9–12 amino acid peptides into the lumen of the endoplasmic reticulum and load these peptides onto major histocompatibility complex class 1 molecules, which are critical for an immune response (18). One possible explanation for their higher levels in the small intestine may stem from the reduced number of microorganisms. The much higher levels of microflora in the large intestine form an additional obstacle for passage of small molecules to the mucosal layer, as bacteria can metabolize and affect the bioavailability of various toxic chemicals (10, 12). Therefore the requirements for the TAP1/TAP2 complex, and the closely related Abcb9, could be diminished. With time, the function of these transporters and the biological purpose for this differential expression in the gut will undoubtedly be revealed.
Abcg5 and Abcg8, which are associated with sitosterolemia and the selective transport of sterol compounds (3), are highly expressed in the small intestine and found at much lower levels in the colon. This suggests that the selection process for the efflux of plant sterols vs. cholesterol from enterocytes back to the intestinal lumen is restricted to the small intestine and would not occur to a significant extent in the large intestine. The relative stability of mRNA expression in the duodenum, jejunum, and ileum would suggest that this active selection process could occur equivalently along the entire length of the small intestine; however, this will need to be examined via functional transport studies.
Abcc3 protein analysis provided additional information that is important in understanding the role of this differentially expressed transporter in the GIT. As indicated above, Rost and colleagues (26) found that Abcc3 (MRP3) was most highly expressed in the colon of the rat intestine. Our findings indicate that MRP3 is also highly expressed in the murine colon at both the mRNA and protein levels. Furthermore, the similar cellular location (basolateral in enterocytes) found between the mouse and rat further supports the notion of a high degree of conservation for ABC transporters amongst eukaryotes. This suggests that MRP3 may have a similar role in the ATP-dependent transport of 17ß-glucuronosyl estradiol, glucuronosyl bilirubin, monovalent bile salts (taurocholate and glycocholate), and sulfated bile salts (i.e., taurochenodeoxycholate-3-sulfate, taurolithocholate-3-sulfate) from the enterocyte to the blood in all higher mammals.
In conclusion, regional differences in the expression of eight ABC transporters along the mouse intestinal tract were identified and confirmed by both RT-PCR and an in silico comparison with a publicly available cDNA data set. Examining the expression profiles of differentially expressed ABC transporters within the context of all genetic elements present on the microarrays revealed that common promoter elements can be identified and yield important information for deciphering the functions and coordinate regulation of ABC transporters. Furthermore, linking mRNA expression analysis with immunohistochemistry yields complementary information required for the complete characterization of gene function. These data indicate that mRNA analysis is a necessary first step in understanding tissue- and region-specific gene function, yet herald the necessity to establish higher-throughput tools for the study of ABC transporters at the protein and functional levels, which in combination with gene expression data, will provide the means to fully characterize ABC transporter function in the intestine.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: G. Williamson, Head of Nutrient Bioavailability, Nestlé Research Center, Vers-Chez-Les-Blanc, PO Box 44, CH-1000 Lausanne 26, Switzerland (E-mail: gary.williamson{at}rdls.nestle.com).
10.1152/ physiolgenomics.00150.2003.
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TOPABSTRACTINTRODUCTIONMATERIAL AND METHODSRESULTSDISCUSSIONREFERENCES |
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0.5 and a core similarity of 1.00, with the exception of GATA and ETSF, are depicted. These two elements are included because GATA was found to be significant in the Abcg5/Abcg8 promoter comparison and ETSF is common to all eight transporters. Numbers directly above or below the identified binding sites indicate their start position (base pair) within the predicted promoter region. For reasons of clarity, only those elements present in at least three of the eight putative promote regions are indicated in color: FKHD, Forkhead domain factors; GATA, GATA binding factors; NFKB, nuclear factor kappa B/c-rel; ETSF, human and murine ETS1 factors; XSEC, Xenopus seleno cysteine tRNA activating factor; AP4R, AP4 and related proteins; SORY, SOx/sRY-sex/testis determining and related HMG box factors; MOKF, mouse Kruppel-like factor; PAX6, PAX-4/PAX-6 paired domain binding sites.
