Yu Y, Pieper R

Urine sample preparation in 96-well filter plates to characterize inflammatory and infectious diseases of the urinary tract.

Advances in experimental medicine and biology. 2015-01-01; 883.77-87.

Urine has been an important body fluid source for diagnostic and prognostic biomarkers of diseases for a long time. Technological advances during the last two decades have enabled a fundamental shift from the discovery of candidate protein biomarkers using single-assay platforms to highly parallel liquid chromatography tandem mass spectrometry (LC-MS/MS)-based proteomic analysis platforms. MS/MS-based approaches such as multiple reaction monitoring (MRM) are also being used increasingly for targeted protein biomarker validation. In large part due to the fact that the majority of protein in voided urine is soluble, such studies have focused on the analysis of urine supernatants, whereas the pellets were discarded after centrifugal sedimentation. Urine sediments are of particular value in the analysis of urinary tract infections (UTI). The LC-MS/MS methods now have sufficient resolving power and sensitivity to survey metaproteomes--the entirety of proteins derived from multiple organisms that interact with each other in mutualistic or antagonistic fashion. Challenges of proteomic analysis of urine include the high dynamic range of protein abundance, high levels of protein post-translational modifications, and high quantities of natural protease inhibitors. Recently, a robust and scalable workflow that can parallelize the processing of multiple urinary supernatant and sediment samples was developed and validated in our lab. This method utilizes 96-well format filter-aided sample preparation (96FASP) strategy and was shown to successfully identify large numbers of proteins from urine samples. Processing 10-50 µg total protein in single experiment, LC-MS/MS with a Q-Exactive mass spectrometer resulted in more than 1,100 distinct human protein identifications from urine supernatants, and around 400 microbial and 1,400 human protein identifications from urine sediments. The surveys are a rich data resource not only for biomarker discovery but also to interrogate mechanisms of pathogenesis in the urinary system.

PMID: 25355571