Abstract
Purpose :
To perform a detailed and comparative analysis on expressed proteins of the ocular fluids (aqueous and vitreous) from NZ white rabbits using iTRAQ-based quantitative proteomic approach with nano-liquid chromatography mass spectrometry (nanoLC-MS).
Methods :
Three healthy rabbits were sacrificed to collect the aqueous and vitreous. Total protein concentration of the intraocular fluids was determined with BCA protein assay kit. Collections from aqueous or vitreous were pooled separately and reduced with dithiothreitol, alkylated by incubation with iodoacetamide and digested with modified porcine trypsin. Each digest was derivatised with 8-plex iTRAQ reagent, then pooled after checking for labeling efficiency. Then the pooled-digests were separated by HPLC with gradient elution. Thirty time-based elutes were collected, concentrated, and then ten fractions obtained and analysis performed by nanoLC-MS. The acquired MS data were searched against the rabbit database with ProteinPiloTM.
Results :
78 unique proteins were identified in the aqueous and vitreous from rabbits by nanoLC-MS. Their profiles and relative quantities were very similar in these two ocular fluids. A total of eight proteins were implicated as significantly differentially-expressed by iTRAQ based quantitative proteomics. Four proteins expressed at a higher level in aqueous than vitreous are serum albumin, Serotransferrin, Alpha-1-antiproteinase E and Histidine-rich glycoprotei. Four proteins expressed at a lower level in aqueous are Clusterin, Hemopexin, Alpha-globin, and Apolipoprotein E4.
Conclusions :
We investigated the protein composition and compared relative quantities between the two ocular fluids in rabbits by the iTRAQ-labelling technology in this study. Altered concentration of several proteins present in the fluids is known to associate closely with major diseases of the eye. Further research will be needed on the quantitative proteomics in animal models, especially for the study of disorders of posterior segment.
This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.