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  • 學位論文

建立影像式搜索策略鑑別參與特定性細胞自噬的去泛素化酶

An image-based screening strategy to identify deubiquitinases in selective autophagy

指導教授 : 楊維元
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摘要


細胞自噬 (autophagy) 是一種細胞內的自我分解機制,調控細胞中物質的去與留,分解後並加以循環利用。需要被清除的物質會被自噬小體 (autophagosome)包覆後與溶酶體 (lysosome)結合,進而被溶酶體中的水解酵素分解。在分類上,細胞自噬可以由所吞噬的物質之特定性,而分成非特定性細胞自噬與特定性細胞自噬(nonselective and selective autophagy)。在特定性細胞自噬的過程中,特定的胞中物質,例如:受傷的胞器,會被泛素(ubiquitin)標定,進而被特定性細胞自噬受器(selective autophagy receptors) 辨識而形成自噬小體進行吞噬與分解。泛素在這個過程扮演了重要的角色;因此,去泛素化酶(deubiquitinases, DUBs) 在調控這個過程中也是不可或缺。在其中一種特定性細胞自噬,胞器自噬(organellophagy) 中,有部分參與其中的去泛素化酶已經被發現,他們去除標定在將被清除的胞器上的泛素,而抑制了胞器自噬的產生,但也尚有許多參與胞器自噬的去泛素化酶尚未被發掘。先前的研究有利用影像結果找尋去泛素化酶,但其方法並非使用大量、系統化的地毯式搜尋,難免會有漏網之魚。因此我們想要發展出一套以影像為主的搜索策略,在人體近一百種的去泛素化酶中,搜尋在胞器自噬中擔任負調控角色的去泛素化酶。 這套策略假設當目標去泛素化酶過度表現時,標定在受傷胞器上的泛素將會被去泛素化酶切除進而抑制胞器自噬的進行。為了使這套策略能夠系統化搜尋目標,我們首先建立了接上增強型綠色螢光蛋白(EGFP)的去泛素化酶質體庫,並將各質體一一表現於海拉細胞(HeLa cells) 中,並以光破壞的方式誘導特定的胞器自噬產生。接著利用免疫螢光染色(immunofluorescence) 標定出泛素與特定胞器的位置,並利用ScanR影像分析軟體計算每個細胞中的去泛素化酶的表現量與泛素標定在特定胞器上的面積,此二參數應該呈現負相關;也就是當目標去泛素化酶的表現量越高,泛素標定在特定胞器上的面積就越低。這個搜索策略可以只計算在特定胞器上的泛素(而非整個細胞中的泛素);而且由於基因轉染的效率(transfection efficiency)因各個細胞而異,因此以單一細胞為單位,可以在一盤細胞中得到不同的去泛素化酶的表現量,便可由量化分析比較不同去泛素化酶表現量下,泛素標定在特定胞器上的面積。 我們所設計的影像式搜索方法首先由目前了解較詳細的粒線體自噬(mitophagy) 來測試其可行性。我們將已知會抑制粒線體自噬去泛素化酶USP30 表現於海拉細胞中進行測試,確定這個策略是可行的,不過仍有一些問題存在於控制組的實驗結果中,需要進一步的改正。同時,我們也準備了材料,欲將此策略應用在其他種胞器自噬中。質體庫目前已經建立了27個去泛素化酶質體,並且在目前了解不多的溶酶體自噬中測試了10個去泛素化酶,其中兩個有可能是目標,需要進一步的檢測才能確定。總而言之,我們所建立的影像搜索方法經過改正ㄧ些問題後,相信可以應用在鑑定抑制胞器自噬的去泛素化酶過程中。

並列摘要


Autophagy is an intracellular digestion mechanism, termed as “self-eating” processes in quality control of cellular components. Autophagy can be categorized as nonselective and selective autophagy by the specificity of the targeted cargo, which is engulfed by autophagosomes and degraded by fusion of lysosomes. In selective autophagy, specific cellular components, such as organelles, are targeted by ubiquitin (Ub), providing a recognition by selective autophagy receptors for autophagosome formation. Since ubiquitination plays an important role in the targeting of substrates for selective autophagy, especially organelle-autophagy, the deubiquitinases (DUBs), which oppose ubiquitination, can be a key factor for suppressing organelle-autophagy. However, which DUBs are involved in organellophagy remains partially unidentified. In addition, previous studies utilize images in aid of identifying DUBs in selective autophagy, but not in a systematic and statistical ways. Therefore, the goal of the study is to establish an image-based screening strategy to robustly identify which DUBs regulate autophagic organelles turnover from over a hundred DUBs within human genome. The assumption underlying this strategy is that ubiquitination of damaged organelle will be suppressed by the overexpression of the DUBs that regulate organelle autophagy. To enable the strategy systematically, DUBs were first cloned into EGFP vector and overexpressed within HeLa cells. To clearly observe the organelle autophagy in cells, the dye-labeled organelles were specifically damaged by light induction. By quantifying the Ub signal on the damaged organelles with immunofluorescence in a cellular scale by ScanR analysis software, the correlation between EGFP-DUB signal intensity and Ub signal area should be negative with the overexpression of the DUB candidates. This strategy can not only quantify the ubiquitination specifically on the damaged organelles cell by cell, but also acquire different DUB expression level in each cell due to the transfection efficiency. This image-based screening strategy was first examined through parkin-mediated mitophagy, and one of the known DUBs for natively regulating parkin-mediated mitophagy, USP30, was tested in the assays. However, the problem in the EGFP control groups remained to be revised. Meanwhile, we prepared for applying the assay to identify the DUBs that regulate autophagic turnover of other types of organelles. So far, 27 DUBs were prepared, with 9 of them testing in lysophgy, and one DUB in Golgiohagy. There were 2 candidates showed in the lysophagy testing, and further screening need to be done. To sum up, the image-based screening strategy can become a powerful method after validation.

參考文獻


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