Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/21978
Title: A chick retinal proteome database and differential retinal protein expressions during early ocular development
Authors: Lam, TC
Li, KK
Lo, SCL 
Guggenheim, JA
To, CH 
Keywords: Chick
Development
Mass spectrometry
Proteome
Proteomics
Retina
Two-dimensional gel electrophoresis
Issue Date: 2006
Publisher: Amer Chemical Soc
Source: Journal of proteome research, 2006, v. 5, no. 4, p. 771-784 How to cite?
Journal: Journal of Proteome Research 
Abstract: Proteomics approach as a research tool has gained popularity in a growing number of basic and clinical researches. However, proteomic research has yet to gain significant momentum in eye research. Hence, we decided to build a retinal proteome database using postnatal retinal tissue from chick, a commonly used animal model in eye research. Employing 2-D gels with the coverage of 3-10 pH gradients, we were able to resolve hundreds of proteins from young chick retinae. Among them, 155 high abundant proteins were identified by Peptide Mass Fingerprinting (PMF) after the Matrix-Assisted Laser Desorption Ionization-Time-of-Flight Mass Spectrometry (MALDI-TOF MS). These proteins were then classified according to their functions. Making use of the retinal database, we were able to identify several differentially expressed proteins that might be involved in early retinal development by comparing the 2-DE maps of chick retinal tissues (3, 10, and 20 days after hatching). With the current proteomics approach, we not only documented the most abundant soluble proteins in the chick retinal tissue, but also demonstrated the dynamic protein expression changes during early ocular development. This represents one of the first steps in building a complete protein database in chick retinae which is applicable to the study of eye diseases from a few selected protein candidates to the whole proteome. Proteomic technology may provide a high throughput platform for advancing eye research in the feasible future.
URI: http://hdl.handle.net/10397/21978
ISSN: 1535-3893
DOI: 10.1021/pr050280n
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