Microbial Biomarkers for Diagnosing and Predicting Infections in Kidney Transplant Recipients

PROJECT SUMMARY Kidney transplantation improves survival in patients with end-stage kidney disease. Immunosuppression, however, leads to infectious complications which cause significant morbidity and mortality in this fragile population. Infections are mostly diagnosed at the time of clinical presentation and clinical factors do not adequately anticipate infections. Predicting infectious complications is thus an important goal in kidney transplantation to prevent significant morbidity and mortality. The long term goal of this study is to develop comprehensive microbial biomarkers in the stool, blood, and the urine for diagnosing and predicting infections in kidney transplant recipients. Our objectives are: 1) Develop a fecal SCFA assay that predicts the risk for infections 2) Develop blood and urine cfDNA assays that can comprehensively diagnose infections as well as predict the risk for infections. These objectives are inspired by observations from several recent pilot studies: 1) We have found that the fecal abundance of short- chain fatty acid (SCFA) producing bacteria is associated with decreased future development of bacterial and viral infections 2) We have demonstrated that cell-free DNA (cfDNA) profiling in the blood and in the urine can simultaneously detect changes in the microbiome and virome over time and detect infections in transplant recipients. Importantly, with respect to cfDNA profiling, we have developed a novel technique called SIFT-seq to overcome the challenge of environmental contamination in low biomass specimens. By biochemically tagging the biological specimen prior to downstream DNA isolation, we can bioinformatically remove DNA introduced during sample preparation and accurately identify the microbiome and virome in low biomass specimens. In this study, we propose to recruit 300 kidney transplant recipients at the time of transplantation for serial fecal, urine, and blood specimen collections during the first year after transplantation. We will profile the gut microbiome using metagenomic sequencing to identify taxa at the species level and using metabolomic SCFA profiling. In addition, we will profile the blood and urine specimens using our novel technique, SIFT-seq, to identify the blood and urine microbiome and virome with high sensitivity and specificity. In Aim 1, we will determine the fecal bacterial and SCFA profiles that predict the risk of infections in kidney transplant recipients. In Aim 2, we will determine the blood and urine cfDNA profiles that are diagnostic and predictive of infections in kidney transplant recipients. Significance. Establishing microbial biomarkers as predictive of infections will allow for identifying kidney transplant recipients at high risk for infections and will allow for future clinical trials involving preemptive changes in immunosuppression, preemptive antibiotic/antiviral therapies, and/or potential gut microbiota-based therapies to prevent infections in these high risk individuals.