title: Proteomics profiling of urine with surface enhanced laser desorption/ionization time of flight mass spectrometry.
abstract: BACKGROUND
  Urine consists of a complex mixture of peptides and proteins and therefore is an interesting source of biomarkers. Because of its high throughput capacity SELDI-TOF-MS is a proteomics technology frequently used in biomarker studies. We compared the performance of seven SELDI protein chip types for profiling of urine using standard chip protocols.
  
  
  RESULTS
  Performance was assessed by determining the number of detectable peaks and spot to spot variation for the seven array types and two different matrices: SPA and CHCA. A urine sample taken from one healthy volunteer was applied in eight-fold for each chip type/matrix combination. Data were analyzed for total number of detected peaks (S/N > 5). Spot to spot variation was determined by calculating the average CV of peak intensities. In addition, an inventory was made of detectable peaks with each chip and matrix type. Also the redundancy in peaks detected with the different chip/matrix combinations was determined. A total of 425 peaks (136 non-redundant peaks) could be detected when combining the data from the seven chip types and the two matrices. Most peaks were detected with the CM10 chip with CHCA (57 peaks). The Q10 with CHCA (51 peaks), SEND (48 peaks) and CM10 with SPA (48 peaks) also performed well. The CM10 chip with CHCA also has the best reproducibility with an average CV for peak intensity of 13%.
  
  
  CONCLUSIONS
  The combination of SEND, CM10 with CHCA, CM10 with SPA, IMAC-Cu with SPA and H50 with CHCA provides the optimal information from the urine sample with good reproducibility. With this combination a total of 217 peaks (71 non-redundant peaks) can be detected with CV's ranging from 13 to 26%, depending on the chip and matrix type. Overall, CM10 with CHCA is the best performing chip type.
authors.affiliation: University of Groningen, University Medical Centre Groningen, Centre for Medical Biomics, Groningen, The Netherlands. j.roelofsen@med.umcg.nl
authors.forename: Han
authors.initials: H
authors.lastname: Roelofsen
authors.forename: Gloria
authors.initials: G
authors.lastname: Alvarez-Llamas
authors.forename: Marianne
authors.initials: M
authors.lastname: Schepers
authors.forename: Karloes
authors.initials: K
authors.lastname: Landman
authors.forename: Roel J
authors.initials: RJ
authors.lastname: Vonk