Since the development of methods for homologous gene recombination, mouse models have played a central role in research in renal pathophysiology. However, many published and unpublished results show that mice with genetic changes mimicking human pathogenic mutations do not display the human phenotype. These functional differences may stem from differences in gene expression between mouse and human kidneys. However, large scale comparison of gene expression networks revealed conservation of gene expression among a large panel of human and mouse tissues including kidneys. Because renal functions result from the spatial integration of elementary processes originating in the glomerulus and the successive segments constituting the nephron, we hypothesized that differences in gene expression profiles along the human and mouse nephron might account for different behaviors. Analysis of SAGE libraries generated from the glomerulus and seven anatomically defined nephron segments from human and mouse kidneys allowed us to identify 4644 pairs of gene orthologs expressed in either one or both species. Quantitative analysis shows that many transcripts are present at different levels in the two species. It also shows poor conservation of gene expression profiles, with less than 10% of the 4644 gene orthologs displaying a higher conservation of expression profiles than the neutral expectation (p<0.05). Accordingly, hierarchical clustering reveals a higher degree of conservation of gene expression patterns between functionally unrelated kidney structures within a given species than between cognate structures from the two species. Similar findings were obtained for sub-groups of genes with either kidney-specific or housekeeping functions. Conservation of gene expression at the scale of the whole organ and divergence at the level of its constituting sub-structures likely account for the fact that although kidneys assume the same global function in the two species, many mouse “models” of human pathologies do not display the expected phenotype.

Background Although high throughput technologies for gene profiling are reliable tools, sample/tissue heterogeneity limits their outcomes when applied to identify molecular markers. Indeed, inter-sample differences in cell composition contribute to scatter the data, preventing detection of small but relevant changes in gene expression level. To date, attempts to circumvent this difficulty were based on isolation of the different cell structures constituting biological samples. As an alternate approach, we developed a tissue compartment analysis (TCA) method to assess the cell composition of tissue samples, and applied it to standardize data and to identify biomarkers. Methodology/Principal Findings TCA is based on the comparison of mRNA expression levels of specific markers of the different constitutive structures in pure isolated structures, on the one hand, and in the whole sample on the other. TCA method was here developed with human kidney samples, as an example of highly heterogeneous organ. It was validated by comparison of the data with those obtained by histo-morphometry. TCA demonstrated the extreme variety of composition of kidney samples, with abundance of specific structures varying from 5 to 95% of the whole sample. TCA permitted to accurately standardize gene expression level amongst >100 kidney biopsies, and to identify otherwise imperceptible molecular disease markers. Conclusions/Significance Because TCA does not require specific preparation of sample, it can be applied to all existing tissue or cDNA libraries or to published data sets, inasmuch specific operational compartments markers are available. In human, where the small size of tissue samples collected in clinical practice accounts for high structural diversity, TCA is well suited for the identification of molecular markers of diseases, and the follow up of identified markers in single patients for diagnosis/prognosis and evaluation of therapy efficiency. In laboratory animals, TCA will interestingly be applied to central nervous system where tissue heterogeneity is a limiting factor.

Because renin and angiotensin I (ANG I) level are high in the renal circulation, the conversion of ANG I is a critical step in the regulation of glomerular hemodynamics. We studied this conversion by investigating the effect of ANG I on intracellular Ca 2+ concentration ([Ca 2+ ] i ) in rat juxtamedullary glomerular afferent and efferent arterioles (AA and EA, respectively). Two types of EA were considered, thin EA and muscular EA, terminating as peritubular capillaries and vasa rectae, respectively. In all arterioles, ANG I elicited [Ca 2+ ] i elevations. Maximal responses of 171 ± 28 (AA), 183 ± 7 (muscular EA), and 78 ± 11 nM (thin EA) (n = 6), similar to those obtained with ANG II, were observed with 100 nM ANG I. The EC 50 values were 20 times higher for ANG I than for ANG II in AA (10.2 vs. 0.5) and muscular EA (6.8 vs. 0.4 nM) and 150 times higher in thin EA (15.2 vs. 0.1 nM). ANG I effect was blocked by losartan, indicating that AT 1 receptors were involved. The ANG-converting enyzme (ACE) inhibitor lisinopril inhibited the maximal response to ANG I in AA and muscular EA by 75 ± 9% (n = 13) and 70 ± 7% (n = 13), respectively, but had no effect in thin EA (n = 14). The serine protease inhibitor aprotinin, the chymase inhibitor chymostatin, and the cysteine protease inhibitors E64 and leupeptin had no effect on ANG I action. These data show that ANG I effects are mainly mediated by ACE in AA and muscular EA but not in thin EA. The lisinopril-insensitive response may be related to conversion by unknown enzyme(s) and/or to activation of AT 1 receptors by ANG I.