Project description:Assessment of diet currently relies on self-reporting, such as food logs, 24 hour recalls and food frequency questionnaires. Self-reporting of diet is inaccurate due to memory lapses, lying and biased language. A molecular-based approach to assess diet would allow accurate reporting of diet for researchers, medical professionals and patients. We performed metaproteomic analysis of 22 human stool samples collected from four individuals enrolled at the Duke Diet and Fitness Center. Samples were collected between 01Aug19 and 22Nov19. All meals at the Duke Diet and Fitness Center were recorded such that the approximate quantities of each food item consumed are known.
Project description:Urine passes through the entire kidney and urinary tract system starting from the glomerulus and ending to the urethra. Cells in the kidney and urinary tract could be exfoliated from the epithelium into the urine, while leukocyte could infiltrate from the local tissue into the urine, which makes the urine a useful subject for clinical evaluation of relevant diseases. We performed scRNA-seq on voided urine samples. 50–100 mL middle stream urine samples were collected from 12 Chinese healthy adults and combined for droplet-based single-cell RNA sequencing after flow cytometric sorting of live cells. We presented the first single-cell atlas of adult human urine and identified multiple previously unrecognized cell types. Based on our scRNA-seq analysis data, a SOX9+ cell population was identified in adult human urine which we speculated to have progenitor potential.
Project description:Urine passes through the entire kidney and urinary tract system starting from the glomerulus and ending to the urethra. Cells in the kidney and urinary tract could be exfoliated from the epithelium into the urine, while leukocyte could infiltrate from the local tissue into the urine, which makes the urine a useful subject for clinical evaluation of relevant diseases. We performed scRNA-seq on voided urine samples. 50–100 mL middle stream urine samples were collected from 12 Chinese healthy adults and combined for droplet-based single-cell RNA sequencing after flow cytometric sorting of live cells. We presented the first single-cell atlas of adult human urine and identified multiple previously unrecognized cell types. Based on our scRNA-seq analysis data, a SOX9+ cell population was identified in adult human urine which we speculated to have progenitor potential.
Project description:We performed single cell transcriptomic analysis on 17 urine samples obtained from five subjects at two different occasions using both spot and 24-hour urine collection. In addition, we used a combined spot urine samples of five healthy individuals as a control sample. We sequenced a total of 71,667 cells. After quality control and downstream analysis, we found that epithelial cells were the most common cell types in the urine. We were also able to identify most kidney cell types in the urine, such as podocyte, proximal, and collecting duct (CD), in addition to macrophages, monocytes and lymphocytes.
Project description:Genome wide DNA methylation profiling of urine and blood samples from patients with diabetic chronic kidney disease. The Illumina Infinium MethylationEPIC BeadChip kit was used to obtain DNA methylation profiles across approximately 850,000 CpGs. Samples included two urine and four buffy coat samples from adults with diabetic chronic kidney disease.
Project description:Urinary extracellular vesicle (EV)-derived microRNAs (miRNAs) have emerged as promising noninvasive biomarkers for disease prediction. However, fluctuations in urine concentration throughout the day may influence miRNA abundance and profiles, potentially limiting their clinical utility. To ensure the broader applicability of urinary miRNAs in disease prediction, it is essential that their profiles remain stable regardless of collection time. In this study, we systematically examined factors influencing urinary miRNA abundance and assessed the stability of miRNA profiles. We collected serial urine samples from healthy individuals over three days, and performed small RNA sequencing to analyze urinary miRNA profiles in relation to various urine concentration parameters. Total miRNA counts were negatively correlated with urine volume and positively correlated with urine concentration indicators, including specific gravity and creatinine levels. miRNA profiles remained stable across different times and days when samples with low miRNA counts were excluded. These findings indicate that urine dilution—primarily due to fluid intake—is a major cause of variation in urinary miRNA abundance. Our results highlight the importance of collecting adequately concentrated samples and provide foundational insights for developing standardized urine collection protocols to enhance the reliability of urinary miRNAs as biomarkers.
Project description:Fifty patient urine samples diagnosed as high-grade urothelial carcinoma (HGUC) or benign were evaluated for bladder cancer via urine cytology. RNA was isolated and analyzed by microarray to identify a panel of biomarkers differentially expressed in HGUC and benign.
Project description:Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.