Kyeong Eun Yang " /> " /> " /> S oon Choi " /> " /> Seung-Hoon Lee" /> Junsoo Park *" /> and Ik-Soon Jang *
" /> Kyeong Eun Yang, Joseph Kwon, Ji-Heon Rhim, Jong Soon Choi, Seung Il Kim, Seung-Hoon Lee, Junsoo Park*, and Ik-Soon Jang *" /> Kyeong Eun Yang, Joseph Kwon, Ji-Heon Rhim, Jong Soon Choi, Seung Il Kim, Seung-Hoon Lee, Junsoo Park*, and Ik-Soon Jang *. Mol. Cells 2011;32:99-106. https://doi.org/10.1007/s10059-011-0064-0">Mol. Cells 2011; 32(1): 99-106
Published online May 11, 2011
https://doi.org/10.1007/s10059-011-0064-0
© The Korean Society for Molecular and Cellular Biology
Kyeong Eun Yang1,7, Joseph Kwon2,7, Ji-Heon Rhim3, Jong Soon Choi1,4, Seung Il Kim1, Seung-Hoon Lee5, Junsoo Park6,*, and Ik-Soon Jang 1,*
Correspondence to : *Correspondence: junsoo@yonsei.ac.kr (JP); jangiksn@gmail.com (ISJ)
The extracellular matrix (ECM) provides an essential structural framework for cell attachment, proliferation, and differentiation, and undergoes progressive changes during senescence. To investigate changes in protein expression in the extracellular matrix between young and senescent fibroblasts, we compared proteomic data (LTQ-FT) with cDNA microarray results. The peptide counts from the proteomics analysis were used to evaluate the level of ECM protein expression by young cells and senescent cells, and ECM protein expression data were compared with the microarray data. After completing the comparative analysis, we grouped the genes into four categories. Class I included genes with increased expression levels in both analyses, while class IV contained genes with reduced expression in both analyses. Class II and Class III contained genes with an inconsistent expression pattern. Finally, we validated the comparative analysis results by examining the expres-sion level of the specific gene from each category using Western blot analysis and semi-quantitative RT-PCR. Our results demonstrate that comparative analysis can be used to identify differentially expressed genes.
Keywords extracellular matrix, microarray, proteomics
Mol. Cells 2011; 32(1): 99-106
Published online July 31, 2011 https://doi.org/10.1007/s10059-011-0064-0
Copyright © The Korean Society for Molecular and Cellular Biology.
Kyeong Eun Yang1,7, Joseph Kwon2,7, Ji-Heon Rhim3, Jong Soon Choi1,4, Seung Il Kim1, Seung-Hoon Lee5, Junsoo Park6,*, and Ik-Soon Jang 1,*
1Division of Life Science, Korea Basic Science Institute, Daejeon 305-333, Korea, 2Korea Basic Science Institute, Gwangju Center, Gwangju 500-757, Korea, 3Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul 110-799, Korea, 4Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon 305-764, Korea, 5Department of Biological Science, Yong-In University, Yongin 449-719, Korea, 6Division of Biological Science and Technology, Yonsei University, Wonju 220-100, Korea, 7These authors contributed equally to this work.
Correspondence to:*Correspondence: junsoo@yonsei.ac.kr (JP); jangiksn@gmail.com (ISJ)
The extracellular matrix (ECM) provides an essential structural framework for cell attachment, proliferation, and differentiation, and undergoes progressive changes during senescence. To investigate changes in protein expression in the extracellular matrix between young and senescent fibroblasts, we compared proteomic data (LTQ-FT) with cDNA microarray results. The peptide counts from the proteomics analysis were used to evaluate the level of ECM protein expression by young cells and senescent cells, and ECM protein expression data were compared with the microarray data. After completing the comparative analysis, we grouped the genes into four categories. Class I included genes with increased expression levels in both analyses, while class IV contained genes with reduced expression in both analyses. Class II and Class III contained genes with an inconsistent expression pattern. Finally, we validated the comparative analysis results by examining the expres-sion level of the specific gene from each category using Western blot analysis and semi-quantitative RT-PCR. Our results demonstrate that comparative analysis can be used to identify differentially expressed genes.
Keywords: extracellular matrix, microarray, proteomics
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