Dataset Information

Kidney transplant monitoring by urinary flow cytometry: Biomarker combination of T cells, renal tubular epithelial cells, and podocalyxin-positive cells detects rejection.

ABSTRACT: Creatinine and proteinuria are used to monitor kidney transplant patients. However, renal biopsies are needed to diagnose renal graft rejection. Here, we assessed whether the quantification of different urinary cells would allow non-invasive detection of rejection. Urinary cell numbers of CD4⁺ and CD8⁺ T cells, monocytes/macrophages, tubular epithelial cells (TEC), and podocalyxin(PDX)-positive cells were determined using flow cytometry and were compared to biopsy results. Urine samples of 63 renal transplant patients were analyzed. Patients with transplant rejection had higher amounts of urinary T cells than controls; however, patients who showed worsening graft function without rejection had similar numbers of T cells. T cells correlated with histological findings (interstitial inflammation p?=?0.0005, r?=?0.70; tubulitis p?=?0.006, r?=?0.58). Combining the amount of urinary T cells and TEC, or T cells and PDX⁺ cells, yielded a significant segregation of patients with rejection from patients without rejection (all p?

SUBMITTER: Goerlich N

PROVIDER: S-EPMC6972704 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Kidney transplant monitoring by urinary flow cytometry: Biomarker combination of T cells, renal tubular epithelial cells, and podocalyxin-positive cells detects rejection.

Goerlich Nina N Brand Hannah Antonia HA Langhans Valerie V Tesch Sebastian S Schachtner Thomas T Koch Benjamin B Paliege Alexander A Schneider Wolfgang W Grützkau Andreas A Reinke Petra P Enghard Philipp P

Scientific reports 20200121 1

Creatinine and proteinuria are used to monitor kidney transplant patients. However, renal biopsies are needed to diagnose renal graft rejection. Here, we assessed whether the quantification of different urinary cells would allow non-invasive detection of rejection. Urinary cell numbers of CD4<sup>+</sup> and CD8<sup>+</sup> T cells, monocytes/macrophages, tubular epithelial cells (TEC), and podocalyxin(PDX)-positive cells were determined using flow cytometry and were compared to biopsy results. ...[more]

PMID: 31964937

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Project description:BackgroundUrine exosomes are small vesicles exocytosed into the urine by all renal epithelial cell types under normal physiologic and disease states. Urine exosomal proteins may mirror disease specific proteome perturbations in kidney injury. Analysis methodologies for the exosomal fraction of the urinary proteome were developed for comparing the urinary exosomal fraction versus unfractionated proteome for biomarker discovery.MethodsUrine exosomes were isolated by centrifugal filtration of urine samples collected from kidney transplant patients with and without acute rejection (AR), which were biopsy matched. The proteomes of unfractionated whole urine (Uw) and urine exosomes (Ue) underwent mass spectroscopy-based quantitative proteomics analysis. The proteome data were analyzed for significant differential protein abundances in AR.ResultsA total of 1018 proteins were identified in Uw and 349 proteins in Ue. Two hundred seventy-nine overlapped between the two urinary compartments and 70 proteins were unique to the Ue compartment. Of 349 exosomal proteins identified from transplant patients, 220 had not been previously identified in the normal Ue fraction. Eleven Ue proteins, functionally involved in an inflammatory and stress response, were more abundant in urine samples from patients with AR, three of which are exclusive to the Ue fraction. Ue AR-specific biomarkers (1) were also detected in Uw, but since they were observed at significantly lower abundances in Uw, they were not significant for AR in Uw.ConclusionA rapid urinary exosome isolation method and quantitative measurement of enriched Ue proteins was applied. Perturbed proteins in the exosomal compartment of urine collected from kidney transplant patients were specific to inflammatory responses, and were not observed in the Ue fraction from normal healthy subjects. Ue-specific protein alterations in renal disease provide potential mechanistic insights and offer a unique panel of sensitive biomarkers for monitoring AR.

Project description:Genetic toxicity testing assesses the potential of compounds to cause DNA damage. There are many genetic toxicology screening assays designed to assess the DNA damaging potential of chemicals in early drug development aiding the identification of promising drugs that have low-risk potential for causing genetic damage contributing to cancer risk in humans. Despite this, in vitro tests generate a high number of misleading positives, the consequences of which can lead to unnecessary animal testing and/or the abandonment of promising drug candidates. Understanding chemical Mode of Action (MoA) is vital to identifying the true genotoxic potential of substances and, therefore, the risk translation into the clinic. Here we demonstrate a simple, robust protocol for staining fixed, human-lymphoblast p53 proficient TK6 cells with antibodies against ɣH2AX, p53 and pH3S28 along with DRAQ5™ DNA staining that enables analysis of un-lysed cells via microscopy approaches such as imaging flow cytometry. Here, we used the Cytek® Amnis® ImageStream®X Mk II which provides a high-throughput acquisition platform with the sensitivity of flow cytometry and spatial morphological information associated with microscopy. Using the ImageStream manufacturer's software (IDEAS® 6.2), a masking strategy was developed to automatically detect and quantify micronucleus events (MN) and characterise biomarker populations. The gating strategy developed enables the generation of a template capable of automatically batch processing data files quantifying cell-cycle, MN, ɣH2AX, p53 and pH3 populations simultaneously. In this way, we demonstrate how a multiplex system enables DNA damage assessment alongside MN identification using un-lysed cells on the imaging flow cytometry platform. As a proof-of-concept, we use the tool chemicals carbendazim and methyl methanesulphonate (MMS) to demonstrate the assay's ability to correctly identify clastogenic or aneugenic MoAs using the biomarker profiles established.

Dataset Information

Kidney transplant monitoring by urinary flow cytometry: Biomarker combination of T cells, renal tubular epithelial cells, and podocalyxin-positive cells detects rejection.

Publications

Kidney transplant monitoring by urinary flow cytometry: Biomarker combination of T cells, renal tubular epithelial cells, and podocalyxin-positive cells detects rejection.

Similar Datasets

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