Ontology highlight
ABSTRACT:
PROVIDER: PRJNA521072 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8537160.fastq.gz | Fastqsanger.gz | |||
| SRR8537170.fastq.gz | Fastqsanger.gz | |||
| SRR8537180.fastq.gz | Fastqsanger.gz | |||
| SRR8537190.fastq.gz | Fastqsanger.gz | |||
| SRR8537200.fastq.gz | Fastqsanger.gz |
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Project description:Urine is a non-invasive biofluid for the identification of biomarkers to detect disease. In particular extracellular vesicles (EVs) have gained increased interest as a biomarker source, because the molecular content is protected against degradation. Clinical implementation on a daily basis requires protocols that inevitably includes short-term storage of the clinical samples, especially when samples are collected at home. However, little is known about the effect of delayed processing on the urinary EVs and their proteome. In the current study, we evaluated two different storage protocols. First, urine stored at 4˚C without any preservative, and second, a protocol compatible with at-home collection, urine with 40 mM EDTA stored at room temperature. For both conditions it was determined whether storage for 0, 2, 4 and 8 days leads to a change in the global urinary EV proteome profile using proteomics based on data-independent acquisition mass spectrometry. We show that EDTA does not affect the global proteome. Remarkably, the EV proteome was stable in both urine stored up to a week at room temperature with EDTA and in urine stored at 4˚C. These findings open up biomarker studies in urine collected via self-sampling.
2022-05-04 | PXD024324 | Pride
Project description:There is a lack of comprehensive studies documenting the impact of sample collection conditions on metabolic composition of human urine. To address this issue, two experiments were performed at a three-month interval, in which midstream urine samples from healthy individuals were collected, pooled, divided into several aliquots and kept under specific conditions (room temperature, 4 °C, with or without preservative) up to 72 h before storage at -80 °C. Samples were analyzed by high-performance liquid chromatography coupled to high-resolution mass spectrometry and bacterial contamination was monitored by turbidimetry. Multivariate analyses showed that urinary metabolic fingerprints were affected by the presence of preservatives and also by storage at room temperature from 24 to 72 hours, whereas no change was observed for urine samples stored at 4 °C over a 72-hour period. Investigations were then focused on 280 metabolites previously identified in urine: 19 of them were impacted by the kind of sample collection protocol in both experiments, including 12 metabolites affected by bacterial contamination and 7 exhibiting poor chemical stability. Finally, our results emphasize that the use of preservative prevents bacterial overgrowth, but does not avoid metabolite instability in solution, whereas storage at 4 °C inhibits bacterial overgrowth at least over a 72-hour period and slows the chemical degradation process. Consequently, and for further LC/MS analyses, human urine samples should be maintained at 4 °C if their collection is performed over 24 hours.
2014-12-18 | MTBLS148 | MetaboLights
Project description:Sepsis remains a diagnostic challenge with no gold-standard test. Urine provides a readily available, non-invasive biofluid with significant diagnostic potential. Urinary gene expression has been previously used for diagnosis and prognosis of urological malignancies and transplant allograft rejections, but remains unutilized for sepsis diagnosis. In this study, the authors use urinary gene expression profiles to both diagnose sepsis and characterize its pathophysiology. By using differential expression augmented with machine learning ensembles, the authors identify a collection of cellular mRNA from 239 genes in patient urine which show exceptional power in classifying septic patients from those with chronic systemic disease in both internal and independent external validation cohorts. Functional analysis indexes the disrupted biological pathways in early sepsis and additionally reveals key molecular networks driving its pathogenesis. This study serves a pioneering step towards expanding the clinical potential of urinary molecular profiles for application to systemic diseases.
2020-02-20 | GSE112099 | GEO
Project description:Sepsis remains a diagnostic challenge with no gold-standard test. Urine provides a readily available, non-invasive biofluid with significant diagnostic potential. Urinary gene expression has been previously used for diagnosis and prognosis of urological malignancies and transplant allograft rejections, but remains unutilized for sepsis diagnosis. In this study, the authors use urinary gene expression profiles to both diagnose sepsis and characterize its pathophysiology. By using differential expression augmented with machine learning ensembles, the authors identify a collection of cellular mRNA from 239 genes in patient urine which show exceptional power in classifying septic patients from those with chronic systemic disease in both internal and independent external validation cohorts. Functional analysis indexes the disrupted biological pathways in early sepsis and additionally reveals key molecular networks driving its pathogenesis. This study serves a pioneering step towards expanding the clinical potential of urinary molecular profiles for application to systemic diseases.
2020-02-20 | GSE112098 | GEO
Project description:Background: Renal cell carcinoma (RCC) accounts for about 2% of all cancers. Renal biopsy is the gold standard among the diagnostic tools, but it is invasive and not suitable for all patients. Therefore, new reliable and non-invasive biomarkers for ccRCC detection are required. Secretion of extracellular vesicles (EVs), containing RNA molecules that can be transferred between cells, seems to be a general characteristic of malignant transformation. Consistently, cancer-derived EVs are enriched in the blood, urine and various malignant effusions of cancer patients. Therefore, urinary samples can be a non-invasive approach for discovering diagnostic biomarkers. Methods: We enrolled 33 clear-cell RCC (ccRCC) patients and 22 healthy subjects (HS), age and sex-matched, for urine collection and extracellular vesicles isolation by differential centrifugation. Transcriptional profiles of urinary EVs from 12 patients with ccRCC and 11 HS were generated using the Illumina HumanHT-12 v4 BeadChip oligonucleotide arrays. Microarray analysis led to the identification of RNA that were then validated using RT-qPCR. Results: We showed for the first time that urinary exosomal shuttle RNA (esRNA) was significantly different in ccRCC patients compared to HS and we identified three EVs esRNA involved in the tumor biology that are potentially suitable as non-invasive biomarkers. GSTA1, CEBPA and PCBD1 RNA levels decreased in urinary EVs of patients compared to HS. After 1 month post-operation, the levels of RNA increased to reach the normal level. Conclusions: This study suggests, for the first time, the potential use of the RNA content of urinary EVs to provide a non-invasive first step to diagnose the ccRCC. Total RNA obtained from urinary extracellular vesicles isolated from ccRCC patients and healthy subjects.
2016-09-01 | E-GEOD-72922 | biostudies-arrayexpress
Project description:To identify urinary RNA from prospective urine as non-invasive biomarkers for kidney transplant patients
2019-03-16 | GSE128347 | GEO
Project description:To identify urinary RNA from biopsy associated urine as non-invasive biomarkers for kidney transplant patients
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Project description:The enteric bacterium Proteus mirabilis is a common cause of complicated urinary tract infections. In the study, microrarrays were used to analyze P. mirabilis gene expression in vivo from experimentally infected mice. Urine was collected at 1, 3, and 7d postinfection, and RNA was isolated from bacteria in the urine for transcriptional analysis. Across 9 microarrays, 471 genes were upregulated and 82 were downregulated in vivo compared to in vitro broth culture. Genes upregulated in vivo encoded MR/P fimbriae, urease, iron uptake systems, amino acid and peptide transporters, pyruvate metabolism, and portions of the TCA cycle. Flagella were downregulated. Ammonia assimilation gene glnA (glutamine synthetase) was repressed in vivo while gdhA (glutamate dehydrogenase) was upregulated in vivo. Contrary to our expectations, ammonia availability due to urease activity in P. mirabilis did not drive this gene expression. A gdhA mutant was growth-deficient in minimal medium with citrate as the sole carbon source, and loss of gdhA resulted in a significant fitness defect in the mouse model of urinary tract infection. Unlike Escherichia coli, which represses gdhA and upregulates glnA in vivo and cannot utilize citrate, the data suggest that P. mirabilis uses glutamate dehydrogenase to monitor carbon-nitrogen balance, and this ability contributes to the pathogenic potential of P. mirabilis in the urinary tract. Voided urine from female CBA/J mice infected with Proteus mirabilis was collected and pooled in RNA stabilizing reagent (RNAprotect). Urine was collected at 1, 3, and 7 d postinfection. RNA was isolated from urine and log-phase LB cultures, converted to cDNA, and labeled with CyDye. Three arrays were completed per time point (9 arrays total). Slides were scanned with a ScanArray Express microarray scanner (Perkin Elmer) at 10 μm resolution and quantified using ScanArray Express software. Resulting data were normalized by total intensity and median spot intensities were identified using MIDAS (v. 2.22) software.
2011-11-29 | E-GEOD-25977 | biostudies-arrayexpress