Rapid label-free identification of estrogen-induced differential protein expression in vivo from mouse brain and uterine tissue

快速无标记鉴定小鼠脑和子宫组织中雌激素诱导的体内差异蛋白表达

阅读:8
作者:Laszlo Prokai, Stanley M Stevens Jr, Navin Rauniyar, Vien Nguyen

Abstract

Protein abundance profiling from tissue using liquid chromatography-tandem mass spectrometry-based "shotgun" proteomics and label-free relative quantitation was evaluated for the investigation of estrogen-regulated protein expression in the mouse brain and uterus. Sample preparation involved a 30-min protein extraction in 8 M aqueous urea solution, followed by disulfide reduction, thiol alkylation, and trypsin digestion of the extracted proteins, and was performed on 3-4 mg of tissue to evaluate the suitability of this methodology to expedite the survey of cellular pathways that are affected in vivo by an experimental therapeutic intervention in an animal model. The label-free proteomic approach (spectral counting) was suitable to identify even subtle changes in cortical protein levels and revealed significant estrogen-induced upregulation of ATP synthase (both alpha- and beta-isoforms), aspartate aminotransferase 2, and mitochondrial malate dehydrogenase without any prior subcellular fractionation of the tissue or the use of multidimensional chromatographic separation. The methodology was also suitable to observe various up- and downregulated proteins in the uterine tissue of ovariectomized mice upon treatment with 17beta-estradiol. In addition to confirming a very significant decrease in the abundance of glutathione S-transferase recognized as a marker of estrogen's impact, our studies have also revealed potential new protein markers such as desmin and lumican that are critical components of cytoskeletal arrangement and, hence, regulation of their abundance could contribute to major morphological changes in the uterus occurring upon estrogenic stimulation.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。