title: Normalization and expression changes in predefined sets of proteins using 2D gel electrophoresis: a proteomic study of L-DOPA induced dyskinesia in an animal model of Parkinson's disease using DIGE.
abstract: BACKGROUND
  Two-Dimensional Difference In Gel Electrophoresis (2D-DIGE) is a powerful tool for measuring differences in protein expression between samples or conditions. However, to remove systematic variability within and between gels the data has to be normalized. In this study we examined the ability of four existing and four novel normalization methods to remove systematic bias in data produced with 2D-DIGE. We also propose a modification of an existing method where the statistical framework determines whether a set of proteins shows an association with the predefined phenotypes of interest. This method was applied to our data generated from a monkey model (Macaca fascicularis) of Parkinson's disease.
  
  
  RESULTS
  Using 2D-DIGE we analysed the protein content of the striatum from 6 control and 21 MPTP-treated monkeys, with or without de novo or long-term L-DOPA administration. There was an intensity and spatial bias in the data of all the gels examined in this study. Only two of the eight normalization methods evaluated ('2D loess+scale' and 'SC-2D+quantile') successfully removed both the intensity and spatial bias. In 'SC-2D+quantile' we extended the commonly used loess normalization method against dye bias in two-channel microarray systems to suit systems with three or more channels.Further, by using the proposed method, Differential Expression in Predefined Proteins Sets (DEPPS), several sets of proteins associated with the priming effects of L-DOPA in the striatum in parkinsonian animals were identified. Three of these sets are proteins involved in energy metabolism and one set involved proteins which are part of the microtubule cytoskeleton.
  
  
  CONCLUSIONS
  Comparison of the different methods leads to a series of methodological recommendations for the normalization and the analysis of data, depending on the experimental design. Due to the nature of 2D-DIGE data we recommend that the p-values obtained in significance tests should be used as rankings only. Individual proteins may be interesting as such, but by studying sets of proteins the interpretation of the results are probably more accurate and biologically informative.
authors.affiliation: Department of Pharmaceutical Biosciences, Division of Toxicology, Uppsala University, BMC, Box 594, SE-75124 Uppsala, Sweden. Kim.Kultima@farmbio.uu.se
authors.forename: Kim
authors.initials: K
authors.lastname: Kultima
authors.forename: Birger
authors.initials: B
authors.lastname: Scholz
authors.forename: Henrik
authors.initials: H
authors.lastname: Alm
authors.forename: Karl
authors.initials: K
authors.lastname: Sköld
authors.forename: Marcus
authors.initials: M
authors.lastname: Svensson
authors.forename: Alan R
authors.initials: AR
authors.lastname: Crossman
authors.forename: Erwan
authors.initials: E
authors.lastname: Bezard
authors.forename: Per E
authors.initials: PE
authors.lastname: Andrén
authors.forename: Ingrid
authors.initials: I
authors.lastname: Lönnstedt
mesh_terms: D000818:Animals; D003342:Corpus Striatum / Q000187:drug effects / Q000378:metabolism*; D004195:Disease Models, Animal; D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods*; D007980:Levodopa; D008252:Macaca fascicularis; D009069:Movement Disorders / Q000209:etiology / Q000378:metabolism; D009419:Nerve Tissue Proteins / Q000378:metabolism*; D010302:Parkinson Disease, Secondary / Q000139:chemically induced / Q000378:metabolism*; D020543:Proteome / Q000378:metabolism*
chemical_list: D009419:Nerve Tissue Proteins; D020543:Proteome; D007980:Levodopa