開發質譜法偵測生物代謝體之方法及應用

Abstract

在此論文中，主要是以探討利用質譜法於果蠅卵子與人體汗水等生物檢體代謝物之分析與應用。在論文第一部份，我們藉由果蠅餵食具有穩定同位素碳十三葡萄醣發展活體同位素標定技術並以基質輔助雷射脫附游離質譜法維分析技術，進而取得果蠅的代謝體變化之訊息，自研究之結果中我們發現此方法可獲得果蠅單一卵子之半定量分析資訊。實驗中經餵食全碳十三葡萄糖的果蠅，碳十三同位素可進入果蠅的代謝過程中，在此我們將以目標代謝物－尿苷二磷酸的碳十三標定程度代表代謝速度，藉此標定程度我們發現此方法可反映環境變化對果蠅代謝速度的影響。在分析結果中，我們發現實驗組中調控短暫的日夜顛倒即可立即反應在果蠅卵子之代謝體，實驗組之果蠅卵子中的代謝體與控制組的果蠅卵子的標定程度結果幾乎一樣。而論文的第二部份，開發了一分析人體汗水代謝體之方法，藉由新穎之奈米噴灑脫附電噴灑游離質譜技術偵測以醫療膠布快速可收集來自於皮膚汗水樣品。此方法結合醫療膠布的快速取樣，不需任何前處理步驟即以奈米噴灑脫附電噴灑游離質譜分析。我們首先以自製的奈米噴灑脫附電噴灑游離源分析標準品，以確立此游離源之可行性，接著進行真實樣品汗液的分析，實驗中可以看到和背景梨子有差異的幾支離子峯，然而這些離子峯的確認還有待進一步的分析。並且我們將取樣及分析的過程做最佳化調整，此方法之優點在於可在幾秒鐘即可將樣品收集完成，且可在幾分鐘內完成質譜分析。

In this work, we describe the development of two analytical methods based on mass spectrometry (MS), which are applicable to analysis of metabolites in biological samples: single eggs of fruit flies and human sweat. In the first part, we present mass spectrometric analysis of small metazoan (fruit fly) samples collected after in-vivo labeling with a stable isotope (carbon-13). We have found that matrix-assisted laser desorption/ionization (MALDI)-MS, used in conjunction with the isotopic labeling, enables quasi-quantitative analysis of metabolism. Flies were initially fed with 13C6-glucose, and the carbon-13 label was readily incorporated to primary metabolites. The yields of isotopic labeling of one target metabolite (uridine diphosphate glucose, UDP-Glc) were used as a proxy for the metabolic rates. The labeling – assessed based on the MALDI mass spectra – reflected the treatment applied to the fly stocks. A connection between circadian clock and the egg metabolism could be established. The study shows that a short-term perturbation to the day/night cycle has little effect on the metabolic rates in eggs – as assessed based on the labeling of UDP-Glc. In the second part of this work, we proposed a method for the analysis of sweat metabolites. The method combines facile sampling of sweat and detection by nanospray desorption electrospray ionization (nanoDESI)-MS. The samples were collected by using adhesive plasters as sampling tools, which was followed by nanoDESI-MS detection without any sample pretreatment. In this study, we implemented a home-made nanoDESI source, and tested it using standard compounds. Following a brief optimization of the detection method, the real samples were analyzed. In the resulting nanoDESI mass spectra, we could find peaks, which may correspond to sweat metabolites; however, a thorough identification of these putative metabolites has yet to be conducted. The main advantage of this method is its simplicity: sweat samples can be collected within a few seconds, and the analysis by nanoDESI-MS takes only several minutes.