發(fā)布時間：2018-05-14 00:44

  本文選題：肝臟細胞 + 蛋白質(zhì)組�。� 參考：《中國人民解放軍軍事醫(yī)學(xué)科學(xué)院》2012年博士論文

【摘要】：肝臟是人體內(nèi)最大的腺體，其主要功能包括物質(zhì)代謝、解毒、防御、激素系統(tǒng)穩(wěn)態(tài)、血液存儲和pH調(diào)節(jié)、造血和免疫調(diào)節(jié)等。肝臟由肝實質(zhì)細胞、肝竇內(nèi)皮細胞、枯否細胞和星狀細胞等組成。細胞是肝臟復(fù)雜功能發(fā)揮的基礎(chǔ)，盡管對于這些細胞的研究不少，其蛋白質(zhì)組成并不清楚，在細胞水平的肝臟蛋白質(zhì)組構(gòu)建還沒有進行。隨著高精度質(zhì)譜儀的發(fā)展，高通量規(guī)�；b定真核細胞的蛋白質(zhì)組成為可能。利用生物信息學(xué)方法進行蛋白質(zhì)鑒定和數(shù)據(jù)挖掘，全面系統(tǒng)地描繪細胞表達的蛋白，對理解不同類型細胞的特異功能具有重大意義。基于細胞的蛋白質(zhì)組研究是蛋白質(zhì)組學(xué)研究內(nèi)容之一，也是人類肝臟蛋白質(zhì)組計劃（human liver proteome project，HLPP）的重要組成部分。 本研究欲分離和純化小鼠肝臟的不同細胞，同時構(gòu)建不同細胞的蛋白質(zhì)表達譜。對肝臟內(nèi)的主要細胞類型-肝實質(zhì)細胞蛋白質(zhì)數(shù)據(jù)集進行了深入的挖掘，分析其功能特征。本研究通過系統(tǒng)生物學(xué)的方法對肝臟細胞蛋白質(zhì)組和轉(zhuǎn)錄組進行比較分析，發(fā)現(xiàn)一批和肝臟細胞功能特異性相關(guān)的分子。通過比較細胞膜表面表達的CD分子，以尋找細胞特異性的表面標(biāo)記物。同時，對這些細胞參與的KEGG通路進行比較，發(fā)現(xiàn)丙酮酸代謝通路可能存在實質(zhì)細胞和非實質(zhì)細胞細胞間協(xié)作，這對于理解肝臟細胞在代謝中的相互協(xié)作起重要提示作用。另外，選取通路中的多個分子進行驗證，為我們的假說提供實驗證據(jù)。細胞預(yù)分離方法提高了肝臟蛋白質(zhì)組的覆蓋率，新鑒定出許多以前在肝臟中沒有鑒定出來的蛋白，而其中的一些蛋白質(zhì)缺失功能信息，本研究通過3種方法對這些蛋白質(zhì)進行了功能注釋。 首先，通過2步原位灌流結(jié)合密度梯度和免疫磁珠分選（magnetic activated cell sorting，，MACS）方法對肝臟細胞進行分離純化，通過細胞學(xué)方法和免疫印跡評價細胞純度，建立了細胞制備方法，為后續(xù)實驗獲得足夠數(shù)量和純度的細胞，用于蛋白質(zhì)組表達譜構(gòu)建。我們以C57BL/6J小鼠肝臟為材料，建立了一套從同一組織中同時獲取肝實質(zhì)細胞、肝竇內(nèi)皮細胞、庫否細胞和星狀細胞4種細胞的方法。 第二，構(gòu)建基于SDS-PAGE聯(lián)合膠內(nèi)酶切和LTQ-FT質(zhì)譜鑒定流程的無標(biāo)記定量方法。通過篩選，選擇牛血清白蛋白作為內(nèi)參蛋白。以復(fù)雜樣本作為背景，研究蛋白上樣量和質(zhì)譜相應(yīng)信號關(guān)系。發(fā)現(xiàn)在一定范圍內(nèi)，蛋白上樣量和質(zhì)譜響應(yīng)信號成線性關(guān)系，成功建立了復(fù)雜樣本適用的蛋白質(zhì)組無標(biāo)定量體系。用APEX軟件（absolute protein expressionmeasurements）對質(zhì)譜數(shù)據(jù)進行定量。該軟件利用校正的譜圖計數(shù)對鑒定蛋白進行相對定量，用機器學(xué)習(xí)算法校正不同實驗批次間誤差和肽段理化性質(zhì)不同引起的離子化效率差異，能夠較為精確測量出蛋白質(zhì)在不同細胞內(nèi)的相對表達值。在95%置信度和雙肽段鑒定的數(shù)據(jù)標(biāo)準下，肝臟實質(zhì)細胞中共鑒定到8,060個蛋白質(zhì)，其中4,842個蛋白質(zhì)有定量信息。 第三，對鑒定肝實質(zhì)細胞蛋白質(zhì)的理化性質(zhì)和豐度分布進行分析，發(fā)現(xiàn)代謝酶在肝實質(zhì)細胞中占很大比重，提示其活躍的代謝能力。結(jié)合文獻和GO（Gene Ontology）注釋信息，對細胞中具有重要生理功能的亞蛋白質(zhì)組進行分析，包括CYP450蛋白家族（cytochromeP450）、糖原結(jié)合蛋白、細胞極性相關(guān)蛋白和激酶，其中4個CYP450蛋白和9個細胞極性相關(guān)蛋白為首次在肝臟中鑒定到的蛋白。同時，結(jié)合蛋白質(zhì)相互作用網(wǎng)絡(luò)進行分析，發(fā)現(xiàn)這些亞蛋白質(zhì)組可能參與的生物學(xué)功能。通過和小鼠血漿蛋白質(zhì)組數(shù)據(jù)比較，發(fā)現(xiàn)一些在肝實質(zhì)細胞中高表達，而在血漿中低表達的蛋白，這些蛋白質(zhì)可能作為肝臟損傷的血清候選標(biāo)記物。結(jié)合mRNA表達和蛋白質(zhì)豐度信息，分析不同功能類別蛋白表達模式，發(fā)現(xiàn)維持細胞生存的核心功能基因其mRNA和蛋白質(zhì)表達豐度的相關(guān)性較高，調(diào)控功能相關(guān)的基因其mRNA和蛋白質(zhì)表達豐度的相關(guān)性普遍低。轉(zhuǎn)氨酶、核糖體和染色體蛋白質(zhì)其mRNA和蛋白質(zhì)表達的豐度沒有相關(guān)性。 第四，肝臟細胞蛋白質(zhì)組和轉(zhuǎn)錄組數(shù)據(jù)進行比較，發(fā)現(xiàn)細胞的特異功能特點。通過聚類分析、GO分析和KEGG通路分析，發(fā)現(xiàn)肝臟實質(zhì)細胞主導(dǎo)物質(zhì)和能量代謝、肝竇內(nèi)皮主導(dǎo)物質(zhì)交換、庫否細胞主導(dǎo)免疫以及星狀細胞主導(dǎo)細胞外基質(zhì)組成。通過哺乳動物表型數(shù)據(jù)庫（mammalian phenotype ontology，MPO）分析，發(fā)現(xiàn)4種細胞在不同肝病中發(fā)揮不同作用，這和細胞各自的特異功能特點是相關(guān)的。同時，對鑒定到的細胞表面CD分子進行比較，發(fā)現(xiàn)一批和細胞特異功能相關(guān)的分子，這些分子可能作為肝臟細胞新的細胞膜表面標(biāo)記物，值得后續(xù)驗證。 第五，利用3種最新的功能注釋算法Blast2GO、權(quán)重基因共表達分析（weighted geneco-expression analysis，WGCNA）和Endeavour，分別基于蛋白質(zhì)序列、基因表達和公共數(shù)據(jù)庫整合打分等3種方法，注釋了實質(zhì)細胞中的2,944個功能未知蛋白的功能。其中數(shù)目比較多的有82個膜整合蛋白、59個細胞核蛋白、40個胞漿蛋白和35個線粒體蛋白。為整合利用多種數(shù)據(jù)資源和算法進行蛋白功能注釋做了初步探索。 最后，在通路水平分析通路成員在不同細胞中表達情況，篩選出丙酮酸代謝通路可能在不同細胞間存在協(xié)作，對該通路中的候選分子進行WB驗證。另外，還選取一些表達具有細胞特異性的分子進行驗證。發(fā)現(xiàn)APOA4為肝實質(zhì)細胞特異表達，ACYP1、ACYP2、ME2為非實質(zhì)細胞特異表達，DOK2、IFNGR1為肝實質(zhì)細胞和庫否細胞特異表達，COLEC10主要在肝實質(zhì)細胞和星狀細胞表達。結(jié)合他人報道的轉(zhuǎn)錄組數(shù)據(jù)，進一步說明了這些分子表達的細胞特異性。這些細胞特異marker分子可能反映了其特異的功能，同時為相關(guān)肝病發(fā)生的機制研究提供細胞信息。
[Abstract]:The liver is the largest gland in the human body. Its main functions include material metabolism, detoxification, defense, homeostasis of hormone systems, blood storage and pH regulation, hematopoiesis and immunoregulation. The liver consists of liver parenchyma cells, hepatic sinusoidal endothelial cells, Kupffer cells and stellate cells. Cells are the basis for the complex functions of the liver, although these cells are used for these cells. With the development of the high precision mass spectrometer, it is possible to identify the protein composition of eukaryotic cells with the development of high precision mass spectrometer. The protein identification and data mining of the protein are used in the bioinformatics method, and the cell surface is systematically depicted. The protein is significant for understanding the specific functions of different types of cells. Cell based proteome research is one of the contents of proteomics research, and is also an important part of the human liver proteome project (HLPP).
The purpose of this study is to separate and purify the different cells of the liver of mice, and to construct the protein expression profiles of different cells. The main cell types in the liver, the protein data set of liver parenchyma cells, are deeply excavated and the functional characteristics of the liver cells are analyzed. The study of the liver cell proteome and transcriptional group by the method of systematic biology In comparison, we found a group of molecules associated with the function of the liver cells. By comparing the CD molecules expressed on the surface of the cell membrane to find the specific surface markers of the cells, and to compare the KEGG pathway involved in these cells, and the possible cooperation between the parenchymal and non parenchymal cells may be found in the pyruvate pathway. This plays an important role in understanding the interaction of the liver cells in the metabolism. In addition, a number of molecules in the pathway are selected to provide experimental evidence for our hypothesis. The cell pre separation method improves the coverage of the liver proteome, and a number of new proteins previously identified in the liver have been identified. Some of these proteins lack functional information. In this study, functional annotation of these proteins was carried out in 3 ways.
First, the liver cells were isolated and purified by 2 steps in situ perfusion combined with density gradient and magnetic activated cell sorting (MACS). Cell preparation methods were established by cytological method and immunoblotting to evaluate cell purity. Cells with sufficient quantity and purity were obtained for subsequent test, and used for protein groups. Expression profile construction. We use the C57BL/6J mouse liver as the material to establish a set of methods for the simultaneous acquisition of 4 kinds of cells from the same tissue, the liver parenchyma cells, the hepatic sinusoidal endothelial cells, the cell and the stellate cells.
Second, an unmarked quantitative method based on SDS-PAGE combined enzyme digestion and LTQ-FT mass spectrometry was constructed. Bovine serum albumin was selected as an internal reference protein by screening. The relationship between the amount of protein sample and the corresponding signal of mass spectrometry was studied with complex samples. It has successfully established a standard quantitative system for the protein group that is suitable for complex samples. The quantitative data of mass spectrometry is quantified by the APEX software (absolute protein expressionmeasurements). The software uses the corrected spectrum count to quantify the identification protein, and uses the machine learning method to correct the errors and peptides between different experimental batches. The difference in ionization efficiency caused by different properties can accurately measure the relative expression value of protein in different cells. Under the data standard of 95% confidence and dipeptide segment identification, 8060 proteins are identified in the liver parenchyma cells, of which 4842 proteins have quantitative information.
Third, analysis of the physical and chemical properties and abundance distribution of protein in the liver parenchyma cells, which make up a large proportion of the metabolites in the liver parenchyma cells, and indicate the active metabolic capacity. Combined with the literature and GO (Gene Ontology) annotation information, the subprotein groups with important physiological functions in the cells, including the CYP450 protein family, are analyzed. CytochromeP450, glycogen binding proteins, cell polar related proteins and kinases, of which 4 CYP450 proteins and 9 cell polar related proteins are proteins identified in the liver for the first time. Meanwhile, combined with protein interaction network analysis, it is found that these subgroups may be involved in biological functions. Through and mouse plasma Compared with the protein group data, some proteins with high expression in the liver parenchyma and low expression proteins in the plasma may be used as a candidate marker for the liver injury. In combination with the expression of mRNA and the information of protein abundance, the expression patterns of different functional categories of proteins are analyzed, and the core functional gene for the maintenance of cell survival is found to be the M The correlation between RNA and protein expression abundance is high, and the correlation of mRNA and protein expression abundances of regulatory function related genes is generally low. There is no correlation between the abundances of the mRNA and protein expression of the transaminase, ribosome and chromosome protein.
Fourth, the liver cell proteome and the transcriptional group were compared, and the specific functional characteristics of the cells were found. By cluster analysis, GO analysis and KEGG pathway analysis, the leading substance and energy metabolism of the liver parenchyma cells, the exchange of the leading substance in the hepatic sinusoid endothelium, the cell main immunity and the composition of the extracellular matrix dominated by stellate cells were found. After the analysis of the Mammalian Phenotype Ontology (MPO), we found that 4 cells play different roles in different liver diseases, which are related to the specific functional characteristics of the cells. At the same time, a group of identified molecules on the cell surface are compared, and a group of molecules related to cell specific functions are found, these molecules may be found. As a new marker for liver cell membrane, it is worthy of further validation.
Fifth, using the 3 most recent functional annotation algorithms Blast2GO, weight gene co expression analysis (weighted geneco-expression analysis, WGCNA) and Endeavour, respectively, based on 3 methods of protein sequence, gene expression and public database integration scoring, respectively, to annotate the function of 2944 functional unknown proteins in the essential fine cell. There are 82 membrane integrins, 59 nuclear proteins, 40 cytoplasmic proteins and 35 mitochondrial proteins, which have been preliminarily explored for the integration of various data resources and algorithms for protein functional annotation.
Finally, the expression of the pathway members in different cells was analyzed at the level of the pathway. It was found that the pyruvate metabolic pathway might cooperate in different cells, and the candidate molecules in the pathway were verified by WB. In addition, some molecules expressed with cell specificity were selected to be verified. It was found that APOA4 was a specific expression of liver parenchymal cells, ACY P1, ACYP2, and ME2 are non parenchymal cells specifically expressed, DOK2, IFNGR1 are specific expression of liver parenchyma cells and cell cells. COLEC10 is mainly expressed in liver parenchyma and stellate cells. Combined with the transcriptional data reported by others, the specific expression of these molecules is further illustrated. These specific marker molecules may reflect their specificity. Meanwhile, it can provide cell information for studying the mechanism of the occurrence of liver diseases.

【學(xué)位授予單位】：中國人民解放軍軍事醫(yī)學(xué)科學(xué)院
【學(xué)位級別】：博士
【學(xué)位授予年份】：2012
【分類號】：R329

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