Proteomic analysis of a urinary stone with two layers composed of calcium oxalate monohydrate and uric acid

Plasma levels and urinary excretion of protein Z in patients with urolithiasis

OBJECTIVES

Protein Z (PZ) is a γ-carboxyglutamic acid protein present in plasma that is involved in blood coagulation. Detailed analysis of urinary stones from patients with urolithiasis has revealed that PZ is often found in urinary stones composed of calcium oxalate monohydrate. In this study, we compared blood and urinary PZ concentrations between healthy individuals and patients with urolithiasis.

METHODS

Plasma and urine were collected from healthy individuals and patients with urolithiasis who provided informed consent. PZ was detected as a urinary stone matrix protein in some of the patients. PZ was quantified by ELISA, creatinine was measured by the enzymatic method, and the total protein concentration was measured by the Bradford method.

RESULTS

The plasma PZ level was 2.54 ± 1.02 μg/mL in healthy individuals and that in urolithiasis patients classified by stone history were from 1.16 ± 0.77 to 3.73 ± 1.09 μg/mL, which was not significantly different. The urinary excretion of PZ (PZ/creatinine) was also not different in patients with urolithiasis and in healthy individuals (from 54.1 ± 40.9 to 95.4 ± 69.4 ng/mg vs. 73.3 ± 36.0 ng/mg). A positive correlation was found between the plasma PZ level and creatinine-corrected urinary PZ concentration (r = 0.46).

CONCLUSIONS

Both the plasma level and urinary excretion of PZ in urolithiasis patients were not significantly different with normal individuals. PZ detected in urinary stones as a matrix protein is thought to be incorporated into urinary stones regardless of blood and urine levels of PZ.

The biomarkers discovery of hyperuricemia and gout: proteomics and metabolomics

Background

Hyperuricemia and gout are a group of disorders of purine metabolism. In recent years, the incidence of hyperuricemia and gout has been increasing, which is a severe threat to people's health. Several studies on hyperuricemia and gout in proteomics and metabolomics have been conducted recently. Some literature has identified biomarkers that distinguish asymptomatic hyperuricemia from acute gout or remission of gout. We summarize the physiological processes in which these biomarkers may be involved and their role in disease progression.

Methodology

We used professional databases including PubMed, Web of Science to conduct the literature review. This review addresses the current landscape of hyperuricemia and gout biomarkers with a focus on proteomics and metabolomics.

Results

Proteomic methods are used to identify differentially expressed proteins to find specific biomarkers. These findings may be suggestive for the diagnosis and treatment of hyperuricemia and gout to explore the disease pathogenesis. The identified biomarkers may be mediators of the link between hyperuricemia, gout and kidney disease, metabolic syndrome, diabetes and hypertriglyceridemia. Metabolomics reveals the main influential pathways through small molecule metabolites, such as amino acid metabolism, lipid metabolism, or other characteristic metabolic pathways. These studies have contributed to the discovery of Chinese medicine. Some traditional Chinese medicine compounds can improve the metabolic disorders of the disease.

Conclusions

We suggest some possible relationships of potential biomarkers with inflammatory episodes, complement activation, and metabolic pathways. These biomarkers are able to distinguish between different stages of disease development. However, there are relatively few proteomic as well as metabolomic studies on hyperuricemia and gout, and some experiments are only primary screening tests, which need further in-depth study.

Proteomic analysis reveals some common proteins in the kidney stone matrix

Background

Proteins are the most abundant component of kidney stone matrices and their presence may reflect the process of the stone’s formation. Many studies have explored the proteomics of urinary stones and crystals. We sought to comprehensively identify the proteins found in kidney stones and to identify new, reliable biomolecules for use in nephrolithiasis research.

Methods

We conducted bioinformatics research in November 2020 on the proteomics of urinary stones and crystals. We used the ClusterProfiler R package to transform proteins into their corresponding genes and Ensembl IDs. In each study we located where proteomic results intersected to determine the 20 most frequently identified stone matrix proteins. We used the Human Protein Atlas to obtain the biological information of the 20 proteins and conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analysis to explore their biological functions. We also performed immunohistochemistry to detect the expression of the top five stone matrix proteins in renal tissue.

Results

We included 19 relevant studies for analysis. We then identified 1,409 proteins in the stone matrix after the duplicates were removed. The 20 most-commonly identified stone matrix proteins were: S100A8, S100A9, uromodulin, albumin, osteopontin, lactotransferrin, vitamin K-dependent protein Z, prothrombin, hemoglobin subunit beta, myeloperoxidase, mannan-binding lectin serine protease 2, lysozyme C, complement C3, serum amyloid P-component, cathepsin G, vitronectin, apolipoprotein A-1, eosinophil cationic protein, fibrinogen alpha chain, and apolipoprotein D. GO and KEGG analysis revealed that these proteins were typically engaged in inflammation and immune response.Immunohistochemistry of the top five stone matrix proteins in renal tissue showed that the expression of S100A8, S100A9, and osteopontin increased, while uromodulin decreased in kidney stone patients. Albumin was rarely expressed in the kidney with no significant difference between healthy controls and kidney stone patients.

Conclusion

Proteomic analysis revealed some common inflammation-related proteins in the kidney stone matrix. The role of these proteins in stone formation should be explored for their potential use as diagnostic biomarkers and therapeutic targets for urolithiasis.

Differential bound proteins and adhesive capabilities of calcium oxalate monohydrate crystals with various sizes

Adhesion of calcium oxalate (CaOx) crystals onto renal tubular epithelial cells is one of the critical steps in kidney stone formation. However, effects of crystal size on the crystal adhesive capability remained unclear. This study compared the adhesive capabilities of CaOx monohydrate (COM) crystals with various sizes (<10 μm, 20-30 μm, 50-60 μm, and > 80 μm). Crystal-cell adhesion assay showed size-dependent increase of COM crystal adhesion onto epithelial cell surface using the larger crystals. Identification of apical membrane proteins that could bind to COM crystals by tandem mass spectrometry (nanoLC-ESI-ETD MS/MS) demonstrated size-specific sets of the COM crystal-binding proteins. Among these, numbers of known oxalate-binding proteins and COM crystal receptors were greatest in the set of the largest size (>80 μm). Atomic force microscopy (AFM) revealed that adhesive forces between carboxylic-immobilized AFM tip and COM crystal surface and between COM-mounted AFM tip and renal epithelial cell surface were size-dependent (greater for the larger crystals). In summary, the adhesive capability of COM crystals is size-dependent - the larger the greater adhesive capability. These data may help better understanding of the pathogenic mechanisms of kidney stone formation at an initial stage when renal tubular cells are exposed to various sizes of COM crystals.

Linking 24-h urines to clinical phenotypes: what alternatives does the future bring?

PURPOSE OF REVIEW

The 24-h urine test is recommended as part of the metabolic evaluation for patients with nephrolithiasis to guide preventive interventions. However, this test may be challenging to interpret and has limits in its predictive ability. In this review, we summarize and discuss the most recent research on the opportunities and challenges for utilizing urinary biomarkers for kidney stone prevention.

RECENT FINDINGS

Contemporary studies utilizing the 24-h urine test have improved our understanding of how to better administer testing and interpret test results. Beyond the standard panel of 24-h urine parameters, recent applications of proteomics and metabolomics have identified protein and metabolic profiles of stone formers. These profiles can be assayed in future studies as potential biomarkers for risk stratification and prediction. Broad collaborative efforts to create large datasets and biobanks from kidney stone formers will be invaluable for kidney stone research.

SUMMARY

Recent advances in our understanding of kidney stone risk have opened opportunities to improve metabolic testing for kidney stone formers. These strategies do not appear to be mutually exclusive of 24-h urine testing but instead complementary in their approach. Finally, large clinical datasets hold promise to be leveraged to identify new avenues for stone prevention.