Comparison of clean catch and bag urine using LC-MS/MS proteomics in infants

使用 LC-MS/MS 蛋白质组学对婴儿清洁尿液和袋装尿液进行比较

阅读:6
作者:Richard Klaus, Teresa K Barth, Axel Imhof, Franziska Thalmeier, Bärbel Lange-Sperandio

Background

Urinary proteomics identifies the totality of urinary proteins and can therefore help in getting an early and precise diagnosis of various pathological processes in the kidneys. In infants, non-invasive urine collection is most commonly accomplished with a urine bag or clean catch. The influence of those two collection

Conclusion

Urinary proteomics shows a high correlation with minor variation in low-abundant proteins between the two urine collection methods. The biological characteristics overrule this variation. Graphical abstract A higher resolution version of the Graphical abstract is available as

Methods

Thirty-two urine samples were collected in infants using urine bag and clean catch within 24 h. Nine boys and seven girls with a mean age of 4.3 ± 2.9 months were included (5 × post-pyelonephritis, 10 × non-kidney disease, 1 × chronic kidney disease (CKD)). Liquid chromatography-mass spectrometry (LC-MS/MS) was performed in data-independent acquisition (DIA) mode. Protein identification and quantification were achieved using Spectronaut.

Results

A total of 1454 urinary proteins were detected. Albumin and α-1-microglobulin were detected the most. The 18 top-abundant proteins accounted for 50% of total abundance. The number of proteins was slightly, but insignificantly higher in clean catch (957 ± 245) than in bag urine (876 ± 255). The median intensity was 1.2 × higher in the clean catch. Overall, differential detection of proteins was 29% between the collection methods; however, it diminished to 3% in the 96 top-abundant proteins. Pearson's correlation coefficient was 0.81 ± 0.11, demonstrating a high intraindividual correlation. A principal component analysis and a heat map showed clustering according to diagnoses and patients rather than to the collection method.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。