Transcriptome-based reconstructions from the murine knockout suggest involvement of the urate transporter, URAT1 (slc22a12), in novel metabolic pathways.

URAT1 (slc22a12) was identified as the transporter responsible for renal reabsorption of the medically important compound, uric acid. However, subsequent studies have indicated that other transporters make contributions to this process, and that URAT1 transports other organic anions besides urate (including several in common with the closely related multi-specific renal organic anion transporters, OAT1 (slc22a6) and OAT3 (slc22a8)). These findings raise the possibility that urate transport is not the sole physiological function of URAT1. We previously characterized mice null for the murine ortholog of URAT1 (mURAT1; previously cloned as RST), finding a relatively modest decrement in urate reabsorptive capacity. Nevertheless, there were shifts in the plasma and urinary concentrations of multiple small molecules, suggesting significant metabolic changes in the knockouts. Although these molecules remain unidentified, here we have computationally delineated the biochemical networks consistent with transcriptomic data from the null mice. These analyses suggest alterations in the handling of not only urate but also other putative URAT1 substrates comprising intermediates in nucleotide, carbohydrate, and steroid metabolism. Moreover, the analyses indicate changes in multiple other pathways, including those relating to the metabolism of glycosaminoglycans, methionine, and coenzyme A, possibly reflecting downstream effects of URAT1 loss. Taken together with the available substrate and metabolomic data for the other OATs, our findings suggest that the transport and biochemical functions of URAT1 overlap those of OAT1 and OAT3, and could contribute to our understanding of the relationship between uric acid and the various metabolic disorders to which it has been linked

Organic Anion and Cation Transporter Expression and Function During Embryonic Kidney Development and in Organ Culture Model Systems

Background Organic anion and cation transporters (OATs, OCTs and OCTNs) mediate the proximal tubular secretion of numerous clinically important compounds, including various commonly prescribed pharmaceuticals. Here, we examine the ontogeny of these transporters in rat embryonic kidney in detail, both in vivo and in two in vitro organ culture models of kidney development, whole embryonic kidney (WEK) culture and culture of induced metanephric mesenchyme (MM). Methods We used QPCR to determine expression levels of transporter genes in rat embryonic kidneys on each day of gestation from ed13 to ed18, in induced and un-induced MM, and on each day of one week of WEK culture. We also used uptake of fluorescein as a novel functional assay of organic anion transporter expression in WEK and MM. Results The developmental induction of the various organic anion and cation transporter genes does not occur uniformly: some genes are induced early (e.g., Oat1 and Oat3, potential early markers of proximal tubulogenesis), and others not till kidney development is relatively advanced (e.g., Oct1, a potential marker of terminal differentiation). We also find that the ontogeny of transporter genes in WEK and MM is similar to that observed in vivo, indicating that these organ culture systems may appropriately model the expression of OATs, OCTs and OCTNs. Conclusion We show that WEK and MM cultures may represent convenient in vitro models for study of the developmental induction of organic anion and cation transporters. Functional organic anion transport as measured by fluorescein uptake was evident by accumulation of the fluorescence in the developing tubule in these organ cultures. By demonstrating the mediated uptake of fluorescein in WEK and MM, we have established a novel in vitro functional assay of transporter function. We find that OATs, OCTs, and OCTNs are differentially expressed during proximal tubule development. Our findings on the renal ontogeny of organic anion and cation transporters could carry implications both for the development of more rational therapeutics for premature infants, as well as for our understanding of proximal tubule differentiation

Differences between knockout and wild-type mice in global gene expression variability.

<p>A, Mean (across the ∼45,000 probe sets) of the differences (△) between knockout and wild-type in log₁₀ CV in each of the 25 datasets analyzed. B, Mean fold change (knockout/wild-type) in CV in the 25 datasets (obtained by exponentiating the corresponding mean △log₁₀ CV values). C, Statistical significance of mean △log₁₀ CV in the 25 datasets, as indicated by the negative log₁₀ of the corresponding <i>p</i> values (termed p<i>p</i> here). (Higher p<i>p</i> values correspond to lower <i>p</i>; e.g., a p<i>p</i> value of 10 indicates <i>p</i> = 10⁻¹⁰ and a p<i>p</i> value of 100 indicates <i>p</i> = 10⁻¹⁰⁰.) Dashed lines denote the usual thresholds of statistical significance: <i>p</i> = 0.05 (corresponding to p<i>p</i> = 1.30), <i>p</i> = 0.01 (p<i>p</i> = 2), & <i>p</i> = 0.001 (p<i>p</i> = 3). Note that the p<i>p</i> values are themselves presented on a log scale so as to enable comparison across their entire range. Numbering of datasets is as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097734#pone-0097734-t001" target="_blank">Table 1:</a> 1, TGFBR2; 2, Pcdh12; 3, Pex5; 4, SRC-2; 5, Arx; 6, Dicer; 7, Mll; 8, Txnrd1; 9, FoxO3; 10, sirtuin 3; 11, Dicer; 12, COX-1; 13, Dicer; 14, Cryptochrome 1 & 2; 15, Phgdh; 16, MFP-2; 17, myostatin; 18, PlagL2; 19, Glycerol kinase; 20, Dicer; 21, Trim24; 22, GalT; 23, Otx2; 24, COX-2; 25, Nix. Error bars in panels A & B denote SEM. △log₁₀ CV, difference between knockout and wild-type in log₁₀ CV; KO, knockout; WT, wild-type; *, datasets affirming use of littermate controls (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097734#pone-0097734-t001" target="_blank">Table 1</a>). Please see the text for details.</p

Gene Expression Omnibus (GEO) datasets analyzed in this paper, ordered by increasing mean △log CV (see Fig. 2).

<p>*Number of biological replicates</p><p>**“y” denotes datasets for which either the GEO annotation or the relevant publication included a specific statement that the knockout and wild-type mice compared were littermates (in the case of the other datasets, the use or not of littermates was not specified).</p

Relationships between sample statistics in a representative microarray dataset of gene expression in wild-type and knockout mice (#19 in Table 1).

<p>A, Log mean gene expression (log mean value for each of the ∼45,000 probe sets on the microarray) in knockout vs. log mean in wild-type. B, Log standard deviation (SD) of gene expression in knockout vs. log SD in wild-type. C, Log CV of gene expression in knockout vs. log CV in wild-type. D, Log SD of expression vs. log mean in wild-type. E, Log CV of expression vs. log mean in wild-type. SD, standard deviation; KO, knockout; WT, wild-type; <i>r</i>, Pearson's correlation coefficient.</p

Characteristics of △log₁₀ CV distributions.

<p>A, Distribution of △log₁₀ CV in three representative datasets (#2, #19, & #25 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097734#pone-0097734-t001" target="_blank">Table 1</a>). Normal curves are superimposed on the histograms; the centers of these curves indicate the positions of the means of the distributions. The solid vertical lines pass through the medians of the distributions and the dashed vertical lines through zero. B, 95% confidence intervals for the differences between the means and medians in the 25 datasets. Numbering of datasets is as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097734#pone-0097734-t001" target="_blank">Table 1:</a> 1, TGFBR2; 2, Pcdh12; 3, Pex5; 4, SRC-2; 5, Arx; 6, Dicer; 7, Mll; 8, Txnrd1; 9, FoxO3; 10, sirtuin 3; 11, Dicer; 12, COX-1; 13, Dicer; 14, Cryptochrome 1 & 2; 15, Phgdh; 16, MFP-2; 17, myostatin; 18, PlagL2; 19, Glycerol kinase; 20, Dicer; 21, Trim24; 22, GalT; 23, Otx2; 24, COX-2; 25, Nix. Please see the text for details.</p

Transcriptome-based reconstructions from the murine knockout suggest involvement of the urate transporter, URAT1 (slc22a12), in novel metabolic pathways.

URAT1 (slc22a12) was identified as the transporter responsible for renal reabsorption of the medically important compound, uric acid. However, subsequent studies have indicated that other transporters make contributions to this process, and that URAT1 transports other organic anions besides urate (including several in common with the closely related multi-specific renal organic anion transporters, OAT1 (slc22a6) and OAT3 (slc22a8)). These findings raise the possibility that urate transport is not the sole physiological function of URAT1. We previously characterized mice null for the murine ortholog of URAT1 (mURAT1; previously cloned as RST), finding a relatively modest decrement in urate reabsorptive capacity. Nevertheless, there were shifts in the plasma and urinary concentrations of multiple small molecules, suggesting significant metabolic changes in the knockouts. Although these molecules remain unidentified, here we have computationally delineated the biochemical networks consistent with transcriptomic data from the null mice. These analyses suggest alterations in the handling of not only urate but also other putative URAT1 substrates comprising intermediates in nucleotide, carbohydrate, and steroid metabolism. Moreover, the analyses indicate changes in multiple other pathways, including those relating to the metabolism of glycosaminoglycans, methionine, and coenzyme A, possibly reflecting downstream effects of URAT1 loss. Taken together with the available substrate and metabolomic data for the other OATs, our findings suggest that the transport and biochemical functions of URAT1 overlap those of OAT1 and OAT3, and could contribute to our understanding of the relationship between uric acid and the various metabolic disorders to which it has been linked