Urinary cell mRNA profiling of kidney allograft recipients: Development of a portable protocol for noninvasive diagnosis of T cell mediated rejection and BK virus nephropathy.

BACKGROUND: We developed urinary cell mRNA profiling for noninvasive diagnosis of acute T cell mediated rejection (TCMR) and BK virus nephropathy (BKVN), two significant post-transplant complications. Our profiling protocol for the multicenter Clinical Trial of Transplantation-04 (CTOT-04) study consisted of centrifugation of urine to prepare cell pellets, washes, addition of an RNA preservative, storage at 800C and shipment in cold containers to our Gene Expression Monitoring (GEM) Core for RNA isolation and quantification of mRNA in RT-qPCR assays. To simplify profiling, we developed a filter-based protocol (ZFBP) that eliminated the need for centrifugation, RNA preservative, storage at 800C, and shipment in cold containers for mRNA profiling. Furthermore, we trained kidney allograft recipients to perform the filtration of urine at home using the filter and post the urinary cell lysate containing the RNA at ambient temperature to our GEM Core for profiling. Here, we report our refinement of ZFBP and investigation of its diagnostic performance characteristics. METHODS: Total RNA was isolated from kidney allograft biopsy-matched urines using a filter-based protocol complemented by a silica-membrane-based cartridge for mRNA enrichment, the Weill Cornell Hybrid Protocol (WCHP). Absolute copy numbers of CD3ε mRNA, CXCL10 mRNA, and 18S rRNA, components of the CTOT-04 three-gene TCMR diagnostic signature, and urinary cell BKV VP 1 mRNA copy number were measured using RT-qPCR assays. Mann-Whitney test, Fischer exact test, and receiver operating characteristic (ROC) curve analysis were used for data analyses. RESULTS: Urinary cell three-gene TCMR diagnostic signature scores in urines processed using the WCHP discriminated kidney allograft recipients with TCMR (12 TCMR biopsies from 11 patients) from those without TCMR or BKVN (29 No TCMR/No BKVN biopsies from 29 patients). The median (25th and 75th percentiles) score of the CTOT-04 three-gene TCMR diagnostic signature was -0.448 (-1.664, 0.204) in the TCMR group and - 2.542 (-3.267, -1.365) in the No TCMR/ No BKVN group (P = 0.0005, Mann-Whitney test). ROC curve analysis discriminated the TCMR group from the No TCMR/ No BKVN group; the area under the ROC curve (AUROC) was 0.84 (95% Confidence Intervals [CI], 0.69 to 0.98) (P < 0.001), and TCMR was diagnosed with a sensitivity of 67% (95% CI, 35 to 89) at a specificity of 86% (95% CI, 67 to 95) using the CTOT-04 validated cutpoint of -1.213 (P = 0.0016, Fisher exact test). BKV VP1 mRNA copy number in urines processed using the WCHP discriminated patients with BKVN (n = 7) from patients without TCMR or BKVN (n = 29) and the AUROC was 1.0 (95% CI, 1.00 to 1.00) (P < 0.0001) and BKVN was diagnosed with a sensitivity of 86% (95% CI, 42 to 99) at a specificity of 100% (95% CI, 85 to 100) with the previously validated cutpoint of 6.5 × 108 BKV-VP1 mRNA copies per microgram of RNA (P < 0.0001, Fisher exact test). CONCLUSION: Urine processed using the WCHP predicted TCMR and BKVN in kidney allograft recipients. WCHP represents not only a significant advance toward the portability of urinary cell mRNA profiling but also improved patient management by minimizing their visits for urine collection.

A Distinct Nasal Microbiota Signature in Peritoneal Dialysis Patients.

Rationale & Objective: The nasal passages harbor both commensal and pathogenic bacteria. In this study, we sought to characterize the anterior nasal microbiota in PD patients using 16S rRNA gene sequencing. Study Design: Cross-sectional. Setting & Participants: We recruited 32 PD patients, 37 kidney transplant (KTx) recipients, 22 living donor/healthy control (HC) participants and collected anterior nasal swabs at a single point in time. Predictors: We performed 16S rRNA gene sequencing of the V4-V5 hypervariable region to determine the nasal microbiota. Outcomes: Nasal microbiota profiles were determined at the genus level as well as the amplicon sequencing variant level. Analytical Approach: We compared nasal abundance of common genera among the 3 groups using Wilcoxon rank sum testing with Benjamini-Hochberg adjustment. DESeq2 was also utilized to compare the groups at the ASV levels. Results: In the entire cohort, the most abundant genera in the nasal microbiota included: Staphylococcus, Corynebacterium, Streptococcus , and Anaerococcus . Correlational analyses revealed a significant inverse relationship between the nasal abundance of Staphylococcus and that of Corynebacterium . PD patients have a higher nasal abundance of Streptococcus than KTx recipients and HC participants. PD patients have a more diverse representation of Staphylococcus and Streptococcus than KTx recipients and HC participants. PD patients who concurrently have or who developed future Staphylococcus peritonitis had a numerically higher nasal abundance of Staphylococcus than PD patients who did not develop Staphylococcus peritonitis. Limitations: 16S RNA gene sequencing provides taxonomic information to the genus level. Conclusions: We find a distinct nasal microbiota signature in PD patients compared to KTx recipients and HC participants. Given the potential relationship between the nasal pathogenic bacteria and infectious complications, further studies are needed to define the nasal microbiota associated with these infectious complications and to conduct studies on the manipulation of the nasal microbiota to prevent such complications.

Urinary cell mRNA profiling of kidney allograft recipients: A systematic investigation of a filtration based protocol for the simplification of urine processing.

BACKGROUND: Kidney transplantation is a life-restorative therapy, but immune rejection undermines allograft survival. Urinary cell mRNA profiles offer a noninvasive means of diagnosing kidney allograft rejection, but urine processing protocols have logistical constraints. We aimed to determine whether the centrifugation-based method for urinary cell mRNA profiling could be replaced with a simpler filtration-based method without undermining quality. METHODS: We isolated RNA from urine collected from kidney allograft recipients using the Cornell centrifugation-based protocol (CCBP) or the Zymo filter-based protocol (ZFBP) and compared RNA purity and yield using a spectrophotometer or a fluorometer and measured absolute copy number of transcripts using customized real-time quantitative PCR assays. We investigated the performance characteristics of RNA isolated using ZFBP and stored either at -80 °C or at ambient temperature for 2 to 4 days and also when shipped to our Gene Expression Monitoring (GEM) Core at ambient temperature. We examined the feasibility of initial processing of urine samples by kidney allograft recipients trained by the GEM Core staff and the diagnostic utility for acute rejection, of urine processed using the ZFBP. RESULTS: RNA purity (P = 0.0007, Wilcoxon matched paired signed-ranks test) and yield (P < 0.0001) were higher with ZFBP vs. CCBP, and absolute copy number of 18S rRNA was similar (P = 0.79) following normalization of RNA yield by reverse transcribing a constant amount of RNA isolated using either protocol. RNA purity, yield, and absolute copy numbers of 18S rRNA, TGF-ß1 mRNA and microRNA-26a were not different (P > 0.05) in the filtrates containing RNA stored either at -80 °C or at ambient temperature for 2 to 4 days or shipped overnight at ambient temperature. RNA purity, yield, and absolute copy numbers of 18S rRNA and TGF-ß1 mRNA were also not different (P > 0.05) between home processed and laboratory processed urine filtrates. Urinary cell levels of mRNA for granzyme B (P = 0.01) and perforin (P = 0.0002) in the filtrates were diagnostic of acute rejection in human kidney allografts. CONCLUSIONS: Urinary cell mRNA profiling was simplified using the ZFBP without undermining RNA quality or diagnostic utility. Home processing by the kidney allograft recipients, the stability of RNA containing filtrates at ambient temperature, and the elimination of the need for centrifuges and freezers represent some of the advantages of ZFBP over the CCBP for urinary cell mRNA profiling.