Overview of kidney and urine proteome databases

Proteomic analysis indicates altered expression of plasma proteins in a rat nephropathy model

BACKGROUND

Minimal-change nephrotic syndrome is an idiopathic disease in which protein leaks through podocytes into the urine. We used proteomic tools to examine differences of plasma protein expression in healthy rats and rats with doxorubicin-induced nephropathy treated with or without prednisone.

METHODS

Healthy three-month-old Sprague-Dawley male rats were randomly chosen for one injection of doxorubicin (5.5 mg/kg) through the caudal vein to induce nephropathy (n = 50) or the same volume of saline (control, n = 20). After 1 week, 25 rats in the nephropathy group received topical prednisone (5.5 mg/kg/day) for 21 days and another 25 rats (untreated nephropathy) and the control rats received topical water. At 4 weeks, protein chips generated from rat plasma samples were analyzed by surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS) to obtain mass-to-charge ratios (m/z) of proteins of 2-50 kDa.

RESULTS

Relative to control rats, untreated nephropathic rats had four significantly higher and seven significantly lower m/z peaks. Prednisone treatment significantly normalized the intensities of peaks 9069 and 15005 (which correspond to cortexin-1 and interleukin-17A, respectively, according to Swiss Prot database) by increasing the expression of 9069 but reducing expression of 15005.

CONCLUSION

Significant differences in plasma proteins can be identified by proteomic analysis using SELDI-TOF-MS in a rat model of nephropathy.

Toward quantitative proteomics of organ substructures: implications for renal physiology

Organs are complex structures that consist of multiple tissues with different levels of gene expression. To achieve comprehensive coverage and accurate quantitation data, organs ideally should be separated into morphologic and/or functional substructures before gene or protein expression analysis. However, because of complex morphology and elaborate isolation protocols, to date this often has been difficult to achieve. Kidneys are organs in which functional and morphologic subdivision is especially important. Each subunit of the kidney, the nephron, consists of more than 10 subsegments with distinct morphologic and functional characteristics. For a full understanding of kidney physiology, global gene and protein expression analyses have to be performed at the level of the nephron subsegments; however, such studies have been extremely rare to date. Here we describe the latest approaches in quantitative high-accuracy mass spectrometry-based proteomics and their application to quantitative proteomics studies of the whole kidney and nephron subsegments, both in human beings and in animal models. We compare these studies with similar studies performed on other organ substructures. We argue that the newest technologies used for preparation, processing, and measurement of small amounts of starting material are finally enabling global and subsegment-specific quantitative measurement of protein levels in the kidney and other organs. These new technologies and approaches are making a decisive impact on our understanding of the (patho)physiological processes at the molecular level.

Proteomics database in chronic kidney disease

Databases which are useful for proteomic analysis of human kidney tissue and urine have been discussed in this article. Integration of the gene-centric and protein-centric general databases with those of human kidney tissue and urine proteomes may open a new window for research in nephrology. Proteins present in the kidney and urine provide basic tools for investigation of kidney function and disease. By comparing such databases between the healthy and diseased populations, we may be able to identify the following: proteins involved in the development of renal disease, proteins involved in progression of CKD, or new biomarker candidate proteins for either the development of renal disease or the progression of CKD.