A simple pattern classification method for alcohol-responsive proteins that are differentially expressed in mouse brain

Bokyung Park, Seul Ki Jeong, Won Suk Lee, Kyung Seong Je, Young Ki Paik

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Proteomic analysis of brain tissues obtained from two inbred mice, C57BL/6J (B6, an alcohol-preferring strain) and DBA/2J (D2, an alcohol-avoiding strain), that were orally administered 1.5 g/kg ethanol, was performed to investigate alcohol-responsive proteins. To analyze relationships of alcohol-responsive protein spots between B6 and D2 mice, we have developed a simple spot classification method (SCM) for the fully matched spot data sets produced by the Melanie 4 analysis software using the paired two-dimensional (2-D) gels of two strains over time. By applying SCM, 55 protein spots that were differentially expressed in brain tissue were classified into 16 patterns as mirror images (2 x 8 patterns), and additionally in an ordered fashion such as 'fast turn over' and 'slow turn over' forms, depending on the frequency of repetition and rate of changed expression profile in 2-D gels over time. Searching for any interaction proteins through databases of interacting proteins using the classified data set has led to the construction of a linkage map, which reveals the interrelationship of the alcohol-responsive proteins between different species. Thus, it is suggested that the different responses for alcohol between B6 and D2 may come from differences of the response rates and interactions of different variants of the alcohol-responsive protein family.

Original languageEnglish
Pages (from-to)3369-3375
Number of pages7
JournalProteomics
Volume4
Issue number11
DOIs
Publication statusPublished - 2004 Nov 1

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Pattern recognition
Brain
Alcohols
Proteins
Gels
Tissue
Protein Databases
Inbred C57BL Mouse
Proteomics
Mirrors
Ethanol
Software

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Molecular Biology

Cite this

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abstract = "Proteomic analysis of brain tissues obtained from two inbred mice, C57BL/6J (B6, an alcohol-preferring strain) and DBA/2J (D2, an alcohol-avoiding strain), that were orally administered 1.5 g/kg ethanol, was performed to investigate alcohol-responsive proteins. To analyze relationships of alcohol-responsive protein spots between B6 and D2 mice, we have developed a simple spot classification method (SCM) for the fully matched spot data sets produced by the Melanie 4 analysis software using the paired two-dimensional (2-D) gels of two strains over time. By applying SCM, 55 protein spots that were differentially expressed in brain tissue were classified into 16 patterns as mirror images (2 x 8 patterns), and additionally in an ordered fashion such as 'fast turn over' and 'slow turn over' forms, depending on the frequency of repetition and rate of changed expression profile in 2-D gels over time. Searching for any interaction proteins through databases of interacting proteins using the classified data set has led to the construction of a linkage map, which reveals the interrelationship of the alcohol-responsive proteins between different species. Thus, it is suggested that the different responses for alcohol between B6 and D2 may come from differences of the response rates and interactions of different variants of the alcohol-responsive protein family.",
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A simple pattern classification method for alcohol-responsive proteins that are differentially expressed in mouse brain. / Park, Bokyung; Jeong, Seul Ki; Lee, Won Suk; Je, Kyung Seong; Paik, Young Ki.

In: Proteomics, Vol. 4, No. 11, 01.11.2004, p. 3369-3375.

Research output: Contribution to journalArticle

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