外周血浆血清和中枢脑区杏仁核的蛋白质组学研究

发布时间：2018-05-21 09:32

本文选题：聚乙二醇分级 + 血浆蛋白质组学　；参考：《重庆医科大学》2017年博士论文

【摘要】：第一部分基于PEG分级联合免疫亲和层析的外周血浆蛋白质组研究研究背景由于血浆成分复杂且蛋白浓度差异较大,血浆蛋白质组学研究难度较大,特别是基于质谱的血浆低丰度蛋白生物标志物研究面临巨大挑战。传统的单一分级方式并不能有效降低血浆的复杂程度,免疫亲和层析也只能有限的提高低丰度蛋白的检测效率。鉴于上述原因,我们通过聚乙二醇分级与免疫亲和层析整合的策略进行人血浆蛋白质组学研究,提高血浆蛋白质的检测效率。方法1.通过聚乙二醇沉淀法对血浆蛋白进行分级:依次用浓度为4%、8%、12%、16%、20%、24%和30%的聚乙二醇溶液进行血浆蛋白质分级。2.免疫亲和层析和质谱检测:将分级处理后的样品进行免疫亲和层析,并利用质谱技术对各组分中的蛋白质进行检测。3.质谱数据分析:通过质谱数据分析,评估聚乙二醇分级联合免疫亲和层析的方法有效性。结果1.通过凝胶染色对比不同浓度聚乙二醇分级效果,发现聚乙二醇浓度为4%时主要包含纤维蛋白原组分,浓度为12%时主要包含免疫球蛋白G组分,浓度为30%时主要包含白蛋白组分。2.聚乙二醇分级有效地将不同理化性质的蛋白质进行了分离,BF组分蛋白质分子量相对较高(45k Da),等电点范围为5-8,CF组分等电点范围4-7。3.通过质谱分析和数据对比,发现聚乙二醇分级联合免疫亲和层析能够提高血浆蛋白质的检测效率(约43%),低丰度蛋白质的检测效率提高约(65.8%)。结论聚乙二醇分级处理联合免疫亲和层析的血浆样品处理策略可以降低血浆蛋白质的复杂程度,提高血浆蛋白质组学的鉴定效率。第二部分基于快速交联和两步沉淀法的血清白蛋白组分析研究背景在血浆蛋白质组学研究中,我们通常会首先去除血清白蛋白等高丰度蛋白质,然而在此过程中与血清白蛋白相互作用的蛋白和肽段也会被去除。这些蛋白和肽段共同组成白蛋白组,且具有重要的病理生理作用,是潜在的疾病生物标志物。亲和吸附和化学沉淀的方法都曾被应用于富集白蛋白组,但是这些方法还有待继续改进。本研究中我们利用快速交联及聚乙二醇和乙醇两步沉淀法富集白蛋白组,以发现更多的有价值的低丰度蛋白质。方法1.甲醛交联,固定相互作用蛋白质:通过对不同浓度和不同交联时间的血清蛋白进行凝胶染色分析,确定甲醛交联的最佳浓度和交联时间。2.聚乙二醇沉淀联合乙醇沉淀富集血清白蛋白:利用凝胶染色分析和免疫印迹分析确定富集血清白蛋白的聚乙二醇和乙醇最适浓度。3.质谱结果生物信息学分析:与前期研究结果进行对比,并构建白蛋白相互作用网络。结果1.通过对比确定最佳的血清交联条件为:甲醛浓度10%,交联时间5秒。2.浓度为12%的聚乙二醇溶液可以有效去除免疫球蛋白G对后续实验的影响。乙醇浓度为57%(PEG4000)和60%(PEG6000)时血清白蛋白的富集效果最好。3.质谱分析共鉴定到171个蛋白质,其中125个蛋白质参与构建白蛋白相互作用网络,直接作用蛋白质21个,间接作用蛋白质104个。质谱结果中有低丰度蛋白质28个,其中12个为首次发现的白蛋白相关蛋白质。结论基于快速交联的聚乙二醇和乙醇两步沉淀法可以有效富集血清白蛋白组,白蛋白组的质谱分析发现新的具有临床诊断价值的低丰度蛋白质。第三部分大鼠中枢脑区杏仁核蛋白质组及其在慢性温和应激下的变化研究背景杏仁核作为中枢神经边缘系统的一部分,可以产生、识别和调节情绪,被称作“情绪脑”,在人类学习、记忆和情感等方面起重要作用,与多种神经精神疾病紧密关联。然而,目前此类疾病(如抑郁症)相关的蛋白质组学研究大多聚焦于海马和前额叶皮层等脑区,而杏仁核研究相对较少。作为抑郁情绪活动调控脑区,杏仁核形态和功能变化与海马和前额叶差异较大,其相关分子调控机制尚需探讨。方法1.构建动物模型,并进行行为学评估:进行为期8周的慢性温和刺激造模,通过糖水偏好实验和强迫游泳实验等行为学检测,得到对照、应激敏感和应激抵抗组。2.定量蛋白质组学分析:采用基于稳定同位素标记的相对和绝对定量(i TRAQ)蛋白组学技术对各组杏仁核的蛋白质表达水平变化进行高通量质谱检测,数据库检索后进行生物信息学分析。3.免疫印迹检测和细胞模型构建:选取感兴趣蛋白进行免疫印迹分析,并构建细胞模型以探讨潜在的分子调控机制。结果1.糖水偏好实验结果提示应激敏感组大鼠糖水偏好程度明显低于对照组和应激抵抗组大鼠,强迫游泳实验结果提示应激敏感组大鼠的不动时间明显长于对照组和应激抵抗组大鼠。2.质谱检测共定量蛋白质2562个,其中102个蛋白质表达存在组间差异。定位和功能分析发现25个(25%)突触相关蛋白质。3.免疫印迹分析:结果显示NMDA和AMPA受体发生了显著性变化,表明杏仁核中谷氨酸能传递受到CMS影响;调节谷氨酸能信号的PSD-95和Ca MKIIβ的表达水平在应激敏感组中呈现增加。此外,涉及谷氨酸摄取的VGlu T1在两个应激组中也显著增加。这些调节和协作分子的变化为应激敏感大鼠杏仁核异常的突触形态和功能可塑性分子机制提供了重要信息。结论该研究所发现的CMS敏感性相关因子(包括Glu N2A/B,PSD-95和Ca MKIIβ)可能为潜在的抗抑郁靶标;慢性温和应激下的杏仁核蛋白质特别是突触蛋白变化将有助于增进我们对抑郁症杏仁核突触可塑性的理解。
[Abstract]:The first part is the research background of peripheral plasma proteome based on PEG classification combined immunoaffinity chromatography. The plasma proteomics research is difficult because of the complex plasma components and high protein concentration differences. Especially, the research on the biomarkers of plasma low abundance protein based on mass spectrometry is facing great challenges. It does not effectively reduce the complexity of plasma, and immunoaffinity chromatography can only improve the detection efficiency of low abundance proteins. In view of the above reasons, we use the strategy of polyethylene glycol classification and immuno affinity chromatography to carry out human plasma proteomics research to improve the detection efficiency of plasma protein. Method 1. through polyb Plasma protein was graded by diol precipitation method: plasma protein fractionation.2. immunoaffinity chromatography and mass spectrometry with 4%, 8%, 12%, 16%, 20%, 24% and 30% polyethylene glycol solutions in order: immuno affinity chromatography was carried out for the samples after the classification, and the.3. mass spectrometry was used to detect the number of proteins in each component by Chromatograph technique. Analysis: through mass spectrometry analysis, the effectiveness of polyethylene glycol classification combined immunoaffinity chromatography was evaluated. Results 1. by gel dyeing compared with different concentrations of polyethylene glycol classification effect, it was found that the concentration of polyethylene glycol 4% mainly contains fibrinogen component, when the concentration is 12%, the main component of the immunoglobulin G component, the concentration is 30%. The proteins of different physicochemical properties were effectively separated by.2. peg classification, the molecular weight of BF components was relatively high (45k Da), the range of isoelectric point was 5-8, and the range 4-7.3. of CF group was analyzed by mass spectrometry and data comparison. It was found that the polyethylene glycol classification combined immunoaffinity chromatography could be extracted. The detection efficiency of high plasma protein (about 43%) and the detection efficiency of low abundance proteins increased by about (65.8%). Conclusion the strategy of plasma sample treatment with PEG grading treatment combined with immuno affinity chromatography can reduce the complexity of plasma protein and improve the identification efficiency of plasma proteomics. The second part is based on rapid crosslinking and two steps. Background in the analysis of serum albumin in precipitation method, we usually remove the high abundance proteins such as serum albumin in plasma proteomics research. However, in this process, the proteins and peptides interacting with serum albumin are also removed. These proteins and peptide segments make up an albumin group and have important diseases. Physical and physiological functions are potential biomarkers of disease. Both affinity adsorption and chemical precipitation have been used to enrich albumin, but these methods remain to be improved. In this study, we have enriched white egg white groups by two step precipitation method with rapid crosslinking, polyethylene glycol and ethanol to find more valuable low abundance eggs. Method 1. formaldehyde crosslinking and immobilization of interaction protein: through gel staining analysis of serum proteins with different concentrations and different crosslinking times, the optimum concentration of formaldehyde crosslinking and crosslinking time.2. precipitation combined with ethanol precipitation and concentration of serum albumin was determined by gel staining analysis and Western blot analysis. Bioinformatics analysis of the optimal concentration of polyethylene glycol and ethanol enriched with serum albumin by.3. mass spectrometry: compared with the previous results and constructing the albumin interaction network. Results 1. through comparison, the optimal serum crosslinking conditions were determined as: the concentration of formaldehyde was 10%, and the polyethylene glycol solution with the concentration of 12% in the crosslinking time of 5 seconds was 12%. The effect of immunoglobulin G on the subsequent experiment was removed. The concentration of serum albumin was 57% (PEG4000) and 60% (PEG6000). The best effect of.3. mass spectrometry was best identified to 171 proteins, of which 125 proteins were involved in the construction of albumin interaction network, 21 direct proteins, 104 indirect proteins. There are 28 low abundance proteins in the fruit, of which 12 are the first discovered albumin related proteins. Conclusion based on the rapid crosslinked polyethylene glycol and ethanol two step precipitation method, the serum albumin group can be enriched effectively. The mass spectrometric analysis of the albumin group found the new low abundance protein with clinical diagnostic value. Third part of the central brain of rats. The amygdala proteome and its changes in chronic mild stress study background the amygdala, as part of the central nervous system, can produce, identify and regulate emotions, known as "emotional brain", play an important role in human learning, memory and emotion, and closely related to a variety of neuromental diseases. However, this is now the case. The proteomics research related to disease like disease (such as depression) is mostly focused on the hippocampus and prefrontal cortex, but the amygdala research is relatively less. As a depressive emotion regulation brain region, the amygdala morphology and function changes are different from the hippocampus and prefrontal lobe, and the related molecular regulation mechanism needs to be discussed. Method 1. the animal model is constructed. .2. quantitative proteomics analysis of stress sensitivity and stress resistance groups: comparative and absolute quantitative (I TRAQ) proteomics techniques based on stable isotopes based on stable isotopes, were performed for 8 weeks of chronic mild stimulation model, by behavioral tests such as sugar water preference and forced swimming tests. The protein expression level of the amygdala was detected by high flux mass spectrometry, and the bioinformatics analysis of.3. immunoblotting and cell model construction were carried out after the database retrieval. The interest protein was selected for Western blot analysis and the cell model was constructed to explore the potential sub regulation mechanism. Results the results of 1. sugar water preference experiment It was suggested that the degree of sugar water preference in the stress sensitive group was significantly lower than that of the control group and the stress resistance group. The forced swimming test showed that the time of the stress sensitive group was significantly longer than that of the control group and the stress resistance group. The 2562 proteins were detected by.2. mass spectrometry, of which 102 proteins were expressed in groups. Functional analysis found 25 (25%).3. immunoblotting analysis of synapse related protein: the results showed that NMDA and AMPA receptors had significant changes, indicating that the energy transfer of glutamate in the amygdala was affected by CMS; the expression level of PSD-95 and Ca MKII beta of glutamate signaling increased in the irritable sensitive group. In addition, it involved glutamate uptake. VGlu T1 also increased significantly in two stress groups. These changes and cooperating molecules provide important information for the synaptic morphology and functional plasticity of the amygdala abnormalities in stress sensitive rats. Conclusion the CMS sensitivity related factors (including Glu N2A/B, PSD-95 and Ca MKII beta) may be potential antitumor agents. The changes of protein in amygdala, especially synaptophysin in chronic mild stress, will help us to understand the synaptic plasticity of amygdala in depression.
【学位授予单位】：重庆医科大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：R749.4

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