Development of sample preparation methods for shotgun proteomic studies of white adipose tissue

• Main Author: Colnoe, Sayda
• Format: Master Thesis
• Language: English
• Published: UiT Norges arktiske universitet 2016
• Subjects: VDP::Medical disciplines: 700::Health sciences: 800; VDP::Medisinske Fag: 700::Helsefag: 800; VDP::Medical disciplines: 700::Basic medical; dental and veterinary science disciplines: 710; VDP::Medisinske Fag: 700::Basale medisinske; odontologiske og veterinærmedisinske fag: 710; VDP::Medical disciplines: 700::Clinical medical disciplines: 750; VDP::Medisinske Fag: 700::Klinisk medisinske fag: 750; dental and veterinary science disciplines: 710::Pharmacology: 728; odontologiske og veterinærmedisinske fag: 710::Farmakologi: 728; FAR-3911; Arctic; Norway
• Online Access: https://hdl.handle.net/10037/9499

Due to the lack of sunlight during the winter, people living in the arctic are unable to produce vitamin D3; hence deficiency of such vitamin is common in this part of the world. Given the geographic location of Norway, development of vitamin D deficiency is a common phenomenon. As vitamin D deficiency has become a public health issue, understanding the effects is vital for clinical implications. Studies have suggested that adipose tissues may be a direct target of vitamin D; especially the role of vitamin D in preventing the formation and development of adipocyte and of which has become of great interest to this study. Therefore, in order to investigate the potential role of vitamin D deficiency in relation to adipose tissue, Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based shotgun analysis of adipose tissue proteome seems appropriate for this study. This research seeks to develop a method that will quantify and identify white adipose tissue proteins. Hence, the appropriate method identify will be used in a vitamin D placebo controlled trial. To address this, the following seven different detergents efficiency methods to extract hydrophobic proteins were compared in triplicates for each sample as follows: PPS Silent (Sodium 3-(4-(1,1-bis (hexyloxy) ethyl) pyridinium-1-yl)- propane-1-sulfonate), ProteaseMAX (Sodium 3-((1-(furan-2-yl) undecyloxy) carbonylamino) propane-1-sulfonate), RapiGest (Sodium 3-[(2-methyl-2-undecyl- 1,3-dioxolan-4-yl) methoxy]- 1-propanesulfonate), Urea-Chaps (Urea-3-[(3-Cholamidopropyl) dimethylammonio]-1-propanesulfonate), SDS (Sodium dodecyl sulfate), SDC (Sodium deoxycholate) and SL (Sodium laurate). Two protein precipitation methods (acetone and ethanol) were compared using SDS and CHAPS-Urea samples as the basis for analysis after the acetone and ethanol precipitation (AP and EtOHP) procedures. Filter-aided sample preparation (FASP) was also carried out on the two samples mentioned above using a 30 kDa filter. The results showed that PPS Silent, ProteaseMAX and RapiGest provided the total highest percentage yielded. Interestingly, SL and SDC yielded higher identification rates of proteins and peptides than the other methods. It is important to mention here that SL and SDC can be useful to anyone working on shotgun proteomics of adipose tissue. This study is intended to be published, and is currently under revision by a publishing group.