Oncotarget

Research Papers:

Quantitative dot blot analysis (QDB), a versatile high throughput immunoblot method

Geng Tian, Fangrong Tang, Chunhua Yang, Wenfeng Zhang, Jonas Bergquist, Bin Wang, Jia Mi, Jiandi Zhang _

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Oncotarget. 2017; 8:58553-58562. https://doi.org/10.18632/oncotarget.17236

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Abstract

Geng Tian1,*, Fangrong Tang2,*, Chunhua Yang1, Wenfeng Zhang2, Jonas Bergquist3, Bin Wang1, Jia Mi1,3 and Jiandi Zhang1,2

1Medicine and Pharmacy Research Center, Binzhou Medical University, Yantai, P. R. China

2Yantai Zestern Biotechnique Co. LTD, Yantai, P. R. China

3Department of Chemistry, BMC, Uppsala University, Uppsala, Sweden

*These authors have contributed equally to this work

Correspondence to:

Jiandi Zhang, email: Jiandi.zhang@zestern.net

Jia Mi, email: jiajiami@gmail.com

Keywords: quantitative dot blot, high throughput, proteomics, immunoblot analysis, western blot

Received: February 17, 2017    Accepted: March 26, 2017    Published: April 19, 2017

ABSTRACT

Lacking access to an affordable method of high throughput immunoblot analysis for daily use remains a big challenge for scientists worldwide. We proposed here Quantitative Dot Blot analysis (QDB) to meet this demand. With the defined linear range, QDB analysis fundamentally transforms traditional immunoblot method into a true quantitative assay. Its convenience in analyzing large number of samples also enables bench scientists to examine protein expression levels from multiple parameters. In addition, the small amount of sample lysates needed for analysis means significant saving in research sources and efforts. This method was evaluated at both cellular and tissue levels with unexpected observations otherwise would be hard to achieve using conventional immunoblot methods like Western blot analysis. Using QDB technique, we were able to observed an age-dependent significant alteration of CAPG protein expression level in TRAMP mice. We believe that the adoption of QDB analysis would have immediate impact on biological and biomedical research to provide much needed high-throughput information at protein level in this “Big Data” era.


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