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Identification of urinary proteins potentially associated with diabetic kidney disease.

ABSTRACT: Diabetic nephropathy (DN) is the most common cause of chronic kidney disease. Although several parameters are used to evaluate renal damage, in many instances, there is no pathological change until damage is already advanced. Mass spectrometry-based proteomics is a novel tool to identify newer diagnostic markers. To identify urinary proteins associated with renal complications in diabetes, we collected urine samples from 10 type 2 diabetes patients each with normoalbuminuria, micro- and macro-albuminuria and compared their urinary proteome with that of 10 healthy individuals. Urinary proteins were concentrated, depleted of albumin and five other abundant plasma proteins and in-gel trypsin digested after prefractionation on sodium dodecyl sulfate polyacrylamide gel electrophoresis. The peptides were analyzed using a nanoflow reverse phase liquid chromatography system coupled to linear trap quadrupole-Orbitrap mass spectrometer. We identified large number of proteins in each group, of which many were exclusively present in individual patient groups. A total of 53 proteins were common in all patients but were absent in the controls. The majority of the proteins were functionally binding, biologically involved in metabolic processes, and showed enrichment of alternative complement and blood coagulation pathways. In addition to identifying reported proteins such as ?2-HS-glycoprotein and Vitamin D binding protein, we detected novel proteins such as CD59, extracellular matrix protein 1 (ECM1), factor H, and myoglobin in the urine of macroalbuminuria patients. ECM1 and factor H are known to influence mesangial cell proliferation, and CD59 causes microvascular damage by influencing membrane attack complex deposition, suggestive their biological relevance to DN. Thus, we have developed a proteome database where various proteins exclusively present in the patients may be further investigated for their role as stage-specific markers and possible therapeutic targets.

SUBMITTER: Marikanty RK

PROVIDER: S-EPMC5131383 | biostudies-literature | 2016 Nov-Dec

REPOSITORIES: biostudies-literature

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Identification of urinary proteins potentially associated with diabetic kidney disease.

Marikanty R K RK Gupta M K MK Cherukuvada S V B SV Kompella S S S SS Prayaga A K AK Konda S S Polisetty R V RV Idris M M MM Rao P V PV Chandak G R GR Dakshinamurty K V KV

Indian journal of nephrology 20161101 6

Diabetic nephropathy (DN) is the most common cause of chronic kidney disease. Although several parameters are used to evaluate renal damage, in many instances, there is no pathological change until damage is already advanced. Mass spectrometry-based proteomics is a novel tool to identify newer diagnostic markers. To identify urinary proteins associated with renal complications in diabetes, we collected urine samples from 10 type 2 diabetes patients each with normoalbuminuria, micro- and macro-al ...[more]

PMID: 27942176

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Project description:In patients with diabetic kidney disease (DKD), plasma renin activity is usually decreased, but there is limited information on urinary renin and its origin. Urinary renin was evaluated in samples from patients with longstanding type I diabetes mellitus and mice with streptozotocin-induced diabetes mellitus. Renin-reporter mouse model (Ren1d-Cre;mT/mG) was made diabetic with streptozotocin to examine whether the distribution of cells of the renin lineage was altered in a chronic diabetic environment. Active renin was increased in urine samples from patients with DKD (n=36), compared with those without DKD (n=38; 3.2 versus 1.3 pg/mg creatinine; P<0.001). In mice with streptozotocin-induced diabetes mellitus, urine renin was also increased compared with nondiabetic controls. By immunohistochemistry, in mice with streptozotocin-induced diabetes mellitus, juxtaglomerular apparatus and proximal tubular renin staining were reduced, whereas collecting tubule staining, by contrast, was increased. To examine the role of filtration and tubular reabsorption on urinary renin, mice were either infused with either mouse or human recombinant renin and lysine (a blocker of proximal tubular protein reabsorption). Infusion of either form of renin together with lysine markedly increased urinary renin such that it was no longer different between nondiabetic and diabetic mice. Megalin mRNA was reduced in the kidney cortex of streptozotocin-treated mice (0.70±0.09 versus 1.01±0.04 in controls, P=0.01) consistent with impaired tubular reabsorption. In Ren1d-Cre;mT/mG with streptozotocin-induced diabetes mellitus, the distribution of renin lineage cells within the kidney was similar to nondiabetic renin-reporter mice. No evidence for migration of cells of renin linage to the collecting duct in diabetic mice could be found. Renin mRNA in microdissected collecting ducts from streptozotocin-treated mice, moreover, was not significantly different than in controls, whereas in kidney cortex, largely reflecting juxtaglomerular apparatus renin, it was significantly reduced. In conclusion, in urine from patients with type 1 diabetes mellitus and DKD and from mice with streptozotocin-induced diabetes mellitus, renin is elevated. This cannot be attributed to production from cells of the renin lineage migrating to the collecting duct in a chronic hyperglycemic environment. Rather, the elevated levels of urinary renin found in DKD are best attributed to altered glomerular filteration and impaired proximal tubular reabsorption.

Project description:BackgroundDiabetic kidney disease (DKD) is a common and potentially fatal consequence of diabetes. Chronic renal failure or end-stage renal disease may result over time. Numerous studies have demonstrated the function of the microbiota in health and disease. The use of advanced urine culture techniques revealed the presence of resident microbiota in the urinary tract, undermining the idea of urine sterility. Studies have demonstrated that the urine microbiota is related with urological illnesses; nevertheless, the fundamental mechanisms by which the urinary microbiota influences the incidence and progression of DKD remain unclear. The purpose of this research was to describe key characteristics of the patients with DKD urinary microbiota in order to facilitate the development of diagnostic and therapeutic for DKD.MethodsWe evaluated the structure and composition of the microbiota extracted from urine samples taken from DKD patients (n = 19) and matched healthy controls (n = 15) using 16S rRNA gene sequencing. Meanwhile, serum metabolite profiles were compared using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Associations between clinical characteristics, urine microbiota, and serum metabolites were also examined. Finally, the interaction between urine microbiota and serum metabolites was clarified based on differential metabolite abundance analysis.ResultsThe findings indicated that the DKD had a distinct urinary microbiota from the healthy controls (HC). Taxonomic investigations indicated that the DKD microbiome had less alpha diversity than a control group. Proteobacteria and Acidobacteria phyla increased in the DKD, while Firmicutes and Bacteroidetes decreased significantly (P < 0.05). Acidobacteria was the most prevalent microbiota in the DKD, as determined by the Linear discriminant analysis Effect Size (LEfSe) plot. Changes in the urinary microbiota of DKD also had an effect on the makeup of metabolites. Short-chain fatty acids (SCFAs) and protein-bound uremic toxins (PBUTs) were shown to be specific. Then we discovered that arginine and proline metabolism was the primary mechanism involved in the regulation of diabetic kidney disease.ConclusionsThis study placed the urinary microbiota and serum metabolite of DKD patients into a functional framework and identified the most abundant microbiota in DKD (Proteobacteria and Acidobacteria). Arginine metabolites may have a major effect on DKD patients, which correlated with the progression of DKD.

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Identification of urinary proteins potentially associated with diabetic kidney disease.

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Identification of urinary proteins potentially associated with diabetic kidney disease.

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