首页 | 本学科首页   官方微博 | 高级检索  
     检索      


A better method for standardizing vitellogenin content of fish tissues
Authors:Ishaque Ali B  Bass Eugene L  Jesien Roman  Hughes Steven  Hupke Carine
Institution:University of Maryland Eastern Shore, Department of Natural Sciences, Carver Hall, Princess Anne, MD 21853, USA. abishaque@mail.umes.edu
Abstract:Vitellogenin (vtg) concentrations were measured in plasma and liver samples from 12 hybrid Tilapia oreochromis niloticus x O. aureus to compare concentrations in these tissues. The results were calculated under two different normalizations: volume per gram of sample used (similar to normalization usually published in the literature and typically used for ELISA) and volume per total protein (similar to normalization used in polyacrylamide gel electrophoresis; PAGE). It was observed that the normalization procedure used in PAGE (per gram total protein) minimized the method detection limit by about 1000 and 2500 times in plasma and liver respectively, compared to the normalization usually reported in the literature. It was also observed that normalizing per gram total protein makes it possible to eliminate a potential problem of accidental dilution of plasma samples during sample collection. Moreover, the normalization on a per gram of total protein makes it possible even to compare results from the two different methods namely PAGE and ELISA. It also allows comparison between different tissues. Using the normalization procedures as used in PAGE (per gram total protein) for liver and the normalization method as reported in literature for ELISA (per volume of sample used), it was observed that liver samples had higher vtg levels (mean: 62 microg vtg/g) compared to the corresponding plasma samples (mean: 0.24 microg vtg/ml). However, when both results were normalized per gram total protein all but one liver sample were lower (62 microg vtg/g) than the corresponding plasma concentrations (mean = 246 microg vtg/g).
Keywords:
本文献已被 PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号