| Literature DB >> 35416493 |
Zihan Zhang1, Rui Zheng1, Zhoutong Chen1, Xia Zhan2, Xiaoliang Fang1, Meizhen Liu3, Yongmei Li3, Yonghu Xu4, Dali Li3, Hongquan Geng1, Xiaohui Zhang5, Guofeng Xu6.
Abstract
Cystinuria is a genetic disorder of cystine transport that accounts for 1-2% of all cases of renal lithiasis. It is characterized by hyperexcretion of cystine in urine and recurrent cystine lithiasis. Defective transport of cystine into epithelial cells of renal tubules occurs because of mutations of the transport heterodimer, including protein b0,+AT (encoded by SLC7A9) and rBAT (encoded by SLC3A1) linked through a covalent disulfide bond. Study generated a novel type B cystinuria rat model by artificially deleting 7 bp of Slc7a9 gene exon 3 using the CRISPR-Cas9 system, and those Slc7a9-deficient rats were proved to be similar with cystinuria in terms of genome, transcriptome, translation, and biologic phenotypes with no off-target editing. Subsequent comparisons of renal histopathology indicated model rats gained typical secondary changes as medullary fibrosis with no stone formation. A total of 689 DEGs (383 upregulated and 306 downregulated) were differentially expressed in the renal cortex of cystinuria rats. In accordance with the functional annotation of DEGs, the potential role of glutathione metabolism processes in the kidney of cystinuria rat model was proposed, and KEGG analysis results showed that knock-out of Slc7a9 gene triggered more biological changes which has not been studied. In short, for the first time, a rat model and its transcriptional database that mimics the pathogenesis and clinical consequences of human type B cystinuria were generated.Entities:
Keywords: CRISPR-Cas9 system; Cystinuria; Renal cortex; SLC7A9; Transcriptional profiling
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Year: 2022 PMID: 35416493 PMCID: PMC9110498 DOI: 10.1007/s00240-022-01321-6
Source DB: PubMed Journal: Urolithiasis ISSN: 2194-7228 Impact factor: 2.861
Fig. 1Generation of heritable Slc7a9-deficient rats using the CRISPR-Cas9 system. A Schematic diagram of Slc7a9-deficient rat model construction using CRISPR-Cas9. The targeted sgRNA sequence at exon 3 is aligned in a single solid line and the PAM sequence is aligned using a double line. B Discriminations of Slc7a9 gene DNA sequence in recombinant clones. SgRNA in blue is labeled by a single line and the PAM in red is indicated by a double line. The dashed line and highlight stand for deletion and insertion of nucleotides, respectively. C Sequencing result of homozygous Slc7a9-deficient and wild-type rats. The missing 7 base pair (bp) sequence is indicated
Fig. 2mRNA and protein expression of cystine transporter Slc7a9/b0,+AT in rat kidney. A Quantitative PCR analysis of rat kidney RNA from different gender, WT (n = 4) and Slc7a9-deficient rats (n = 4), ****P < 0.0001, t-test. B–D Western blot and quantification of protein b0,+AT, encoded by Slc7a9 in WT and Slc7a9-deficient rats. Cropped blots were presented. The samples were derived from the same experiment and gel/blot were processed in parallel. b0,+AT is revealed as one protein band of 53 kD, β-actin is used as a loading control, and appears as one 42kD protein band, **P < 0.01, t-test. E Immunohistochemistry staining of Slc7a9-deficient rat (Left of Fig. 2E) and SD rat (Right of Fig. 2E.b) using Slc7a9 antibody. Black scale bar = 100 μm
Fig. 3Urinary cystine level of Slc7a9-deficient and WT rats. A Comparison of the chromatograms of urinary cystine between Slc7a9-deficient and WT rats. The retention time for cystine in analyte is identical at 1.18 min. B Relative urinary cystine concentration for WT rats of male and female (each sex, n = 5), Slc7a9-deficient rats of male and female (each sex, n = 5). Cystine in urine was measured using liquid chromatography-tandem mass spectrometry. Values are normalized to creatinine measurements. Data are presented as means ± standard error. Significant differences in urinary concentration were determined using Student’s t-test. C Urinary creatinine concentration for WT rats of male and female (each sex, n = 5), Slc7a9-deficient rats of male and female (each sex, n = 5). There is no significant difference between the Slc7a9-deficient and WT groups in male and female rats. D Typical flat hexagonal cystine crystals were observed in urine sediments of 6-month-old Slc7a9-deficient rats that were absent in the sediments of WT rats. The inset is the local magnification. Black scale bar = 100 μm
Fig. 4Evidence of renal injury in Slc7a9-deficient rats. Black and white scale bar = 100 μm. Renal sections stained by Hematoxylin & eosin (HE) staining, Masson’s trichrome staining and TUNEL staining, in comparison of kidney injury level in cortex and medulla of Slc7a9−/− and WT rats. Section of Slc7a9-deficient rat presented mild tubulointerstitial fibrosis (stained in blue). In TUNEL staining, positive cell (green), DAPI (blue), and white arrows pointing the TUNEL and DAPI labeled nuclei. In all pictures, scale bar = 100 μm
Fig. 5RNA-Sequencing (RNA-Seq) analysis of three 6-month-old female Slc7a9-deficient model rats and three WT control rats of the same age, as well as verification. A Statistic of DEGs. 689 are significantly differentially expressed in Slc7a9-deficient model rat (FC = 1.5), 383 of which are up-regulated (red dots) and 306 are down-regulated (blue dots). B Cluster dendrogram and heatmap of differentially expressed mRNA. C Volcano plot of RNA-Seq data. Up-regulated (red dots) and 306 are down-regulated (blue dots). D Gene Ontology enrichment analysis of DEGs. Each classification presents the top 10 GO term by FDR value. E Gene Ontology (GO) enrichment analysis of genes that are differentially expressed in Slc7a9-deficient model rat. Down-regulated GO terms are listed at the left and up-regulated are listed at the right. Bars indicated for -log10 (p-value), polyline indicated for numbers of genes. F Pathways analysis by KEGG database. The top 30 most represented pathways of up- and downregulated pathways in the cortical kidney. Bars indicated for -log10 (p-value), polyline indicated for numbers of genes
Total 60 statistically significant pathways of KEGG analysis, ranked by p-value
| Pathway ID | Pathway | DEG_number | Pvalue |
|---|---|---|---|
| rno00140 | Steroid hormone biosynthesis | 9 | 0.000187 |
| rno05320 | Autoimmune thyroid disease | 8 | 0.000322 |
| rno04940 | Type I diabetes mellitus | 8 | 0.000368 |
| rno05323 | Rheumatoid arthritis | 10 | 0.000482 |
| rno00480 | Glutathione metabolism | 8 | 0.00076 |
| rno05330 | Allograft rejection | 7 | 0.000826 |
| rno05144 | Malaria | 7 | 0.001358 |
| rno05416 | Viral myocarditis | 8 | 0.001437 |
| rno04933 | AGE-RAGE signaling pathway in diabetic complications | 10 | 0.001474 |
| rno04612 | Antigen processing and presentation | 8 | 0.002306 |
| rno00910 | Nitrogen metabolism | 4 | 0.002498 |
| rno05418 | Fluid shear stress and atherosclerosis | 12 | 0.002649 |
| rno05166 | HTLV-I infection | 16 | 0.002684 |
| rno04728 | Dopaminergic synapse | 11 | 0.003059 |
| rno04668 | TNF signaling pathway | 10 | 0.003256 |
| rno04650 | Natural killer cell mediated cytotoxicity | 10 | 0.003961 |
| rno00830 | Retinol metabolism | 7 | 0.004228 |
| rno05150 | Staphylococcus aureus infection | 6 | 0.004789 |
| rno04614 | Renin-angiotensin system | 5 | 0.004877 |
| rno04145 | Phagosome | 12 | 0.005118 |
| rno00350 | Tyrosine metabolism | 5 | 0.005539 |
| rno04380 | Osteoclast differentiation | 10 | 0.006076 |
| rno05167 | Kaposi's sarcoma-associated herpesvirus infection | 13 | 0.006567 |
| rno04514 | Cell adhesion molecules (CAMs) | 11 | 0.008318 |
| rno04974 | Protein digestion and absorption | 8 | 0.009166 |
| rno00982 | Drug metabolism—cytochrome P450 | 6 | 0.009328 |
| rno04926 | Relaxin signaling pathway | 10 | 0.009984 |
| rno04713 | Circadian entrainment | 8 | 0.010422 |
| rno04657 | IL-17 signaling pathway | 8 | 0.010422 |
| rno00983 | Drug metabolism—other enzymes | 7 | 0.011048 |
| rno00120 | Primary bile acid biosynthesis | 3 | 0.014602 |
| rno05031 | Amphetamine addiction | 6 | 0.015153 |
| rno05164 | Influenza A | 11 | 0.015918 |
| rno05168 | Herpes simplex infection | 12 | 0.017247 |
| rno01040 | Biosynthesis of unsaturated fatty acids | 4 | 0.018327 |
| rno04625 | C-type lectin receptor signaling pathway | 8 | 0.01868 |
| rno04918 | Thyroid hormone synthesis | 6 | 0.020207 |
| rno04913 | Ovarian steroidogenesis | 5 | 0.020619 |
| rno04151 | PI3K-Akt signaling pathway | 18 | 0.021211 |
| rno04621 | NOD-like receptor signaling pathway | 10 | 0.024182 |
| rno05134 | Legionellosis | 5 | 0.024191 |
| rno05133 | Pertussis | 6 | 0.024674 |
| rno05140 | Leishmaniasis | 6 | 0.024674 |
| rno04976 | Bile secretion | 6 | 0.024674 |
| rno04060 | Cytokine-cytokine receptor interaction | 15 | 0.024789 |
| rno04979 | Cholesterol metabolism | 5 | 0.026117 |
| rno00360 | Phenylalanine metabolism | 3 | 0.026969 |
| rno04973 | Carbohydrate digestion and absorption | 4 | 0.027518 |
| rno05146 | Amoebiasis | 7 | 0.02787 |
| rno04970 | Salivary secretion | 6 | 0.027991 |
| rno05204 | Chemical carcinogenesis | 6 | 0.031591 |
| rno00340 | Histidine metabolism | 3 | 0.03471 |
| rno04512 | ECM-receptor interaction | 6 | 0.03548 |
| rno00980 | Metabolism of xenobiotics by cytochrome P450 | 5 | 0.037201 |
| rno00512 | Mucin type O-glycan biosynthesis | 3 | 0.038965 |
| rno04610 | Complement and coagulation cascades | 6 | 0.039664 |
| rno04927 | Cortisol synthesis and secretion | 5 | 0.045048 |
| rno05132 | Salmonella infection | 6 | 0.046505 |
| rno04934 | Cushing’s syndrome | 9 | 0.047935 |
| rno00500 | Starch and sucrose metabolism | 3 | 0.048227 |