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中华肾病研究电子杂志 ›› 2020, Vol. 09 ›› Issue (04) : 152 -158. doi: 10.3877/cma.j.issn.2095-3216.2020.04.002

所属专题: 文献

论著

基于单细胞测序及蛋白质组数据分析尿酸转运蛋白在肾脏的精细表达定位
陈小龙1, 迟坤1, 邓翼遥1, 蔡广研1, 陈香美1, 洪权1,()   
  1. 1. 100853 北京,解放军总医院第一医学中心肾脏病科、解放军肾脏病研究所、肾脏疾病国家重点实验室、国家慢性肾病临床医学研究中心、肾脏疾病研究北京市重点实验室
  • 收稿日期:2020-06-15 出版日期:2020-08-28
  • 通信作者: 洪权
  • 基金资助:
    国家自然科学基金面上项目(81870491); 解放军总医院杰出青年人才培育计划(2019-JQPY-002); 国家科技部研发计划政府间合作项目(2018YFE0126600)

Analysis of precision expression localization of uric acid transporters in kidney tissues based on single cell RNA sequencing and proteome data

Xiaolong Chen1, Kun Chi1, Yiyao Deng1, Guangyan Cai1, Xiangmei Chen1, Quan Hong1,()   

  1. 1. Department of Nephrology, First Medical Center of Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases, Beijing 100853, China
  • Received:2020-06-15 Published:2020-08-28
  • Corresponding author: Quan Hong
  • About author:
    Corresponding author: Hong Quan, Email:
引用本文:

陈小龙, 迟坤, 邓翼遥, 蔡广研, 陈香美, 洪权. 基于单细胞测序及蛋白质组数据分析尿酸转运蛋白在肾脏的精细表达定位[J]. 中华肾病研究电子杂志, 2020, 09(04): 152-158.

Xiaolong Chen, Kun Chi, Yiyao Deng, Guangyan Cai, Xiangmei Chen, Quan Hong. Analysis of precision expression localization of uric acid transporters in kidney tissues based on single cell RNA sequencing and proteome data[J]. Chinese Journal of Kidney Disease Investigation(Electronic Edition), 2020, 09(04): 152-158.

目的

利用单细胞测序、微量蛋白质组学及免疫组化三部分数据深入分析肾脏尿酸转运蛋白的细胞分布及表达丰度。

方法

利用2个成人健康肾脏的单细胞测序数据集(GSE131685)分析12个肾脏尿酸转运基因的细胞定位及表达丰度,进一步利用激光微切割联合质谱检测大鼠肾小管14个区段蛋白质数据集12个蛋白的定位和丰度,最后利用ProteinAtlas数据库检索上述蛋白在肾脏中的免疫组化染色结果。

结果

单细胞测序数据集GSE131685中,12个尿酸转运蛋白集中表达于近端小管细胞,而在KIT数据集中,除了ABCG2、SLC22A12和SLC22A13外,其余都集中表达于近端肾小管S1,S2和S3段细胞。KEAT蛋白数据集的分析结果与KIT数据结果类似:ABCG2,SLC17A3,SLC22A12,SLC22A6和SLC22A8在近端小管S1,S2和S3段有显著的表达,尤其是SLC22A6仅富集在S2段肾小管,而ABCG2在S3段有较强的富集,其它的蛋白表达丰度相对较低。ProteinAtlas的免疫组化数据显示出与单细胞测序及蛋白质组的结果有较大的差异:ABCC2、SLC17A4、SLC22A6、SLC22A11、SLC22A12、SLC22A13及SLC2A9显示在近端小管比较特异的表达定位,其中ABCC2、SLC22A6、SLC22A11和SLC22A13信号较强。ABCC4、ABCG2和SLC16A9的表达丰度相对较低,特异性较差。

结论

尿酸转运蛋白在肾脏主要集中表达于小管的S1,S2和S3段细胞,蛋白质组数据和单细胞测序数据比较接近。单细胞测序及微切割的微量蛋白组学是研究蛋白精细定位的良好工具。本研究为今后研究尿酸转运蛋白的功能及研发降尿酸药物提供基础依据。

Objective

To analyze the cell distribution and expression abundance of uric acid transporters in kidney by single cell sequencing, microproteomics, and immunohistochemical data.

Methods

The cell localization and expression abundances of 12 uric acid transporter genes were analyzed by single cell sequencing data sets (GSE131685) of 2 healthy adult kidneys. Furtherly, laser microdissection combined with mass spectrometry was used to detect the localization and abundance of 12 proteins in the protein data set of 14 segments of rat renal tubules. Finally, the immunohistochemical staining results of the above proteins in the kidney were retrieved in the ProteinAtlas database.

Results

In the single-cell sequencing dataset GSE131685, 12 uric acid transporters were concentratedly expressed in proximal tubule cells. In the KIT dataset, except for uric acid transporters of ABCG2、SLC22A12, and SLC22A13, the rest uric acid transporters were concentratedly expressed in proximal tubular cells of S1, S2, and S3 segments. The analysis results of the KEAT protein dataset were similar to those of the KIT dataset: uric acid transporters of ABCG2, SLC17A3, SLC22A12, SLC22A6, and SLC22A8 were significantly expressed in proximal tubule cells of S1, S2, and S3 segments, while uric acid transporter of SLC22A6 was especially enriched in the renal tubule cells of S2 segment, and uric acid transporter of ABCG2 was strongly enriched in the proximal tubule cells of S3 segment. The other proteins showed relatively lower abundance and specificity. Immunohistochemical data of the ProteinAtlas showed results significantly different from those of the single-cell sequencing and proteome: uric acid transporters of ABCC2, SLC17A4, SLC22A6, SLC22A11, SLC22A12, SLC22A13, and SLC2A9 showed a specific localization in proximal tubules, among which the uric acid transporters of ABCC2, SLC22A6, SLC22A11, and SLC22A13 has stronger abundance, while ABCC4, ABCG2, and SLC16A9 showed relatively lower expression abundance and specificity.

Conclusion

Uric acid transporters were mainly expressed in the renal tubule cells of S1, S2, and S3 segments. The results of proteome data and single-cell sequencing data were similar. The microproteomics of single-cell sequencing and laser capture microdissection is an effective tool to study precise localization of proteins. This study provided a basis for future research on the function of uric acid transporters and the development of uric acid-lowering drugs.

表1 负责尿酸转运的常见蛋白
图1 尿酸转运蛋白在人肾脏单细胞测序数据(GSE131685)中的表达情况
图2 健康人肾脏单细胞核测序数据(KIT)中尿酸转运蛋白的表达
图3 9个转运蛋白在14个小管区段上的定位表达蛋白质组鉴定结果
图4 尿酸11个转运蛋白在人肾脏上的定位表达情况(免疫组化,引自http://www.proteinatlas.org)
[1]
Guo W, Yang D, Wu D, et al. Hyperuricemia and long-term mortality in patients with acute myocardial infarction undergoing percutaneous coronary intervention [J]. Ann Transl Med, 2019, 7(22): 636.
[2]
Hong Q, Wu D, Chen XM, et al. Cloning and sequence analysis of human uric acid transporter gene [J]. Di Yi Jun Yi Da Xue Xue Bao, 2005, 25(6): 623-629.
[3]
Puig JG, Torres RJ, De Miguel E, et al. Uric acid excretion in healthy subjects: a nomogram to assess the mechanisms underlying purine metabolic disorders [J]. Metabolism, 2012, 61(4): 512-518.
[4]
Yano H, Tamura Y, Kobayashi K, et al. Uric acid transporter ABCG2 is increased in the intestine of the 5/6 nephrectomy rat model of chronic kidney disease [J]. Clin Exp Nephrol, 2014, 18(1): 50-55.
[5]
Verboom K, Everaert C, Bolduc N, et al. SMARTer single cell total RNA sequencing [J]. Nucleic Acids Res, 2019, 47(16): e93.
[6]
Zang L, Palmer Toy D, Hancock WS, et al. Proteomic analysis of ductal carcinoma of the breast using laser capture microdissection, LC-MS, and 16O/18O isotopic labeling [J]. J Proteome Res, 2004, 3(3): 604-612.
[7]
Liao J, Yu Z, Chen Y, et al. Single-cell RNA sequencing of human kidney [J]. Sci Data, 2020, 7(1): 4.
[8]
Lindstrom NO, De Sena Brandine G, Ransick A, et al. Single-cell RNA sequencing of the adult mouse kidney: from molecular cataloging of cell types to disease-associated predictions [J]. Am J Kidney Dis, 2019, 73(1): 140-142.
[9]
Wu H, Humphreys BD. The promise of single-cell RNA sequencing for kidney disease investigation [J]. Kidney Int, 2017, 92(6): 1334-1342.
[10]
Limbutara K, Chou CL, Knepper MA. Quantitative proteomics of all 14 renal tubule segments in rat [J]. J Am Soc Nephrol, 2020, 31(6): 1255-1266.
[11]
Wu H, Uchimura K, Donnelly EL, et al. Comparative analysis and refinement of human psc-derived kidney organoid differentiation with single-cell transcriptomics [J]. Cell Stem Cell, 2018, 23(6): 869-881.
[12]
Stuart T, Butler A, Hoffman P, et al. Comprehensive integration of single-cell data [J]. Cell, 2019, 177(7): 1888-1902.
[13]
Park J, Shrestha R, Qiu C, et al. Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease [J]. Science, 2018, 360(6390): 758-763.
[14]
Young MD, Mitchell TJ, Vieira Braga FA, et al. Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors [J]. Science, 2018, 361(6402): 594-599.
[15]
Cao J, Wang C, Zhang G, et al. Incidence and simple prediction model of hyperuricemia for urban han chinese adults: a prospective cohort study [J]. Int J Environ Res Public Health, 2017, 14(1): 67.
[16]
Park SH, Shin WY, Lee EY, et al. The impact of hyperuricemia on in-hospital mortality and incidence of acute kidney injury in patients undergoing percutaneous coronary intervention [J]. Circ J, 2011, 75(3): 692-697.
[17]
Braga F, Pasqualetti S, Ferraro S, et al. Hyperuricemia as risk factor for coronary heart disease incidence and mortality in the general population: a systematic review and meta-analysis [J]. Clin Chem Lab Med, 2016, 54(1): 7-15.
[18]
洪权,吴镝,陈香美,等. 人尿酸转运蛋白在肾小管上皮细胞的定位表达研究[J]. 中华肾脏病杂志,2005, 21(9): 527-533.
[19]
Wu H, Malone AF, Donnelly EL, et al. Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response [J]. J Am Soc Nephrol, 2018, 29(8): 2069-2080.
[20]
Hoque KM, Dixon EE, Lewis RM, et al. The ABCG2 Q141K hyperuricemia and gout associated variant illuminates the physiology of human urate excretion [J]. Nat Commun, 2020, 11(1): 2767.
[21]
Togawa N, Miyaji T, Izawa S, et al. A Na-phosphate cotransporter homologue (SLC17A4 protein) is an intestinal organic anion exporter [J]. Am J Physiol Cell Physiol, 2012, 302(11): C1652-C1660.
[22]
Chen J, Suo S, Tam PP, et al. Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq [J]. Nat Protoc, 2017, 12(3): 566-580.
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