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鳕鱼免疫活性肽的可控制备及其免疫活性研究

The Controllable Preparation of Pollock Immunomodulating Peptide and Its Immunity Activity

【作者】 侯虎

【导师】 李八方;

【作者基本信息】 中国海洋大学 , 食品科学, 2011, 博士

【摘要】 免疫活性肽是一类具有增强机体免疫力、增强巨噬细胞吞噬功能、提高机体抵御外界病原体感染能力等免疫功能的肽,具有分子量小、稳定性强,且免疫原性弱、生物活性高等诸多优点。目前酶法制备生物活性肽主要集中在活性优化和动力学模拟上,并不能保证酶解按预期进行。而鳕鱼免疫活性肽的可控制备及免疫活性研究,是通过采用生物技术、生物传感器、数学模型、人工神经网络等实现了免疫活性肽的准确预测、动态监测、可控制备,并且利用树脂吸附技术等对免疫活性肽精制,为免疫活性肽的工业化生产提供理论依据和技术支持。同时本文还对制备的鳕鱼免疫肽的体内免疫活性机理作了初步探讨。本论文形成了以下研究成果:1、本文以鳕鱼加工下脚料鳕鱼排为原料作为研究对象,首先研究了其基本组成。鳕鱼排中蛋白质含量较高(18.4%),以碱溶性蛋白(35.49%)和基质蛋白(30.49%)为主,有重要利用价值。鳕鱼排蛋白中以高含量的甘氨酸(26.51%)和谷氨酸(12.57%)为主,其次为丙氨酸、谷氨酰胺、丝氨酸、亮氨酸和赖氨酸。为了充分利用鳕鱼蛋白,对鳕鱼排进行了软化高压预处理研究,条件最终设定为120℃处理30min。2、水解度值、分子量分布、多肽含量均是反映酶解产物特征的重要因素,但在线监测困难。鳕鱼蛋白酶解产物游离氨基酸含量呈现规律性变化,可作为监测水解反应的响应因子,并且生物传感器测定响应因子速度快、准确度高、稳定性好。其中对谷氨酸和赖氨酸测定的相对误差分别为1.5%和1.0%,变异系数分别为3.85%和3.03%,标准偏差分别为0.78和0.60。多酶切位点下,游离谷氨酸和赖氨酸都呈规律性变化,与水解度正相关,可作为酶解产物的响应因子,同时在一定水解度范围内,游离谷氨酸和赖氨酸浓度与水解度均呈现较好的线性关系。利用游离谷氨酸和赖氨酸浓度作为响应因子监测多种商品酶的水解程度是可行的。3、鳕鱼排的胰酶水解产物(PFH)可以显著促进脾细胞增殖、T细胞增殖、巨噬细胞吞噬(p<0.05)。分子量和水解度是影响脾细胞增殖活性的重要因素。在水解度15-18%时,PFH的脾细胞增殖活性最高。采用响应面方法确定了鳕鱼免疫肽制备参数:蛋白浓度25g/L、pH值8.0、温度(50±1)℃、时间290 min和加酶量24 U/mg,验证实验的平均DH为16.87%,脾淋巴细胞平均增殖率为28.45%,与理论值相符。PFH在220nm和280nm处有较大吸收峰,氨基酸组成以脯氨酸(15.69%)含量最高。PFH在广泛的pH范围具有较好的溶解性,在温度20-60℃范围PFH具有较低的粘度; pH对PFH的起泡性、乳化性影响较大。PFH在胃蛋白酶、胰蛋白酶和复合酶条件下会发生部分降解,但主要多肽成分的变化很小。4、在严格控制水解条件下,动力学模型在一定范围内可以很好的预测反应的进行。鳕鱼蛋白的胰酶水解的动力学模型为:R= (0.1693 E0– 0.2816 S0) exp│-0.357 * DH│,DH= 2.801 ln│1 + (0.06044 E0/S0– 0.1005)t│,胰蛋白酶的失活动力学常数为0.0512 min-1。鳕鱼免疫肽恒定条件时的预测模型:DH= 2.801 ln [1+ 1.35006t],可以通过预测曲线,获得免疫肽的制备时间。这对鳕鱼免疫活性肽制备有十分重要的意义。验证试验表明,当条件恒定时,实现了鳕鱼免疫肽制备的预测性,且模型理论值与实际值相符。但是当条件改变时,如搅拌速率的变化、温度的波动,显著的影响了最终反应产物,模型理论值与实际值不符。5、利用生物传感器,实现了恒定条件和动态条件下鳕鱼免疫制备的监控。恒定条件下,水解度在11-18%时,与游离赖氨酸、谷氨酸呈现很好的线性关系,方程式分别为:DH = 0.2225[Glu] - 5.3097,DH = 0.0126[Lys] - 1.2275。当初始酶浓度或初始底物浓度改变时,谷氨酸、赖氨酸的响应浓度与水解度数学关系不明确,呈现无规律的曲线关系。尽管不能用统一的数学模型确定动态变化的水解反应,但是其反应临界值符合很好的的线性关系,可以用以下公式来表示:[Glu] = 0.8186 [S0] + 0.0346 [E0] + 0.4506,[Lys] = 0.7430 [S0] + 0.1370 [E0] + 5.2931。6、本文利用人工神经网络(BP-ANNs)和生物传感器,建立了三个可在动态变化条件下实现在线监测的网络模型分别为:GLU-BP-ANNs的动态监控模型,LYS-BP-ANNs的动态监控模型,GLU-LYS- BP- ANNs的动态监控模型。三个模型的样本值与拟合值进行比较分析可知,R2值分别为0.9967、0.9964、0.9967,拟合误差范围分别为0-4.14%、0-4.56%、0-4.71%,拟合平均相对误差值分别为1.06%、0.94%、0.99%。利用模型进行五次独立的验证实验,理论值与实验值相符合,试验的相对误差范围分别为0.23%-2.81%,0.26%-1.91%和0.30%-2.35%。三个模型在一定程度上实现了仿真监控,均可以用来监测水解反应的进程。三个网络监控模型的共性参数如下:隐含层为1层,输入层与隐层之间使用logsig传递函数,隐层与输出层之间使用线性purelin函数,网络训练函数采用trainlm,适应性学习函数采用learngdm。GLU-BP-ANNs模型确定的其他参数如下:输入层节点分别为初始酶浓度E0、初始底物浓度S0、游离谷氨酸浓度[Glu];输出层节点为DH;隐层节点数为10。LYS-BP-ANNs模型确定的其他参数如下:输入层节点分别为初始酶浓度E0、初始底物浓度S0、终产物的赖氨酸浓度[Lys];输出层节点为DH;隐层节点数为11。GLU-LYS-BP-ANNs模型确定的其他参数如下:输入层节点分别为初始酶浓度E0、初始底物浓度S0、终产物的[Lys]和[Glu];输出层节点为DH;隐层节点数为8。7、利用Sephadex G-25凝胶柱层析、阳离子色谱、反相高效液相色谱对鳕鱼免疫肽混合成分反复纯化,获得了三个免疫活性肽,并利用反相高效液相色谱C18分析柱纯度鉴定,得到单一对称的单峰。利用Nano-ESI-Ms/Ms分别对三个活性肽进行结构表征。免疫肽Y3的分子量为583.9922Da,为五肽,肽序列为Asn– Gly– Met– Thr– Tyr,在20μg/mL时的脾细胞平均增殖率分别为35.92%。免疫肽H2的分子量为470.1422Da,其肽序列为Asn– Gly– Leu– Ala– Pro,为五肽,在浓度20μg/mL时,脾淋巴细胞增殖率平均值为32.96%。免疫活性肽S4的分子量为305.1622Da,为二肽,其序列为Trp– Thr,在浓度20μg/mL时,脾淋巴细胞增殖率平均值为31.35%。8、本文进一步研究了PFH对正常小鼠、免疫低下小鼠的免疫机理。PFH能显著提高正常小鼠的淋巴细胞转化活性(p<0.05)、迟发型变态反应(p<0.05)和单核巨噬细胞的吞噬能力(p<0.05),而对免疫器官指数和血清溶血素的影响较小(p>0.05)。对于免疫功能低下小鼠,PFH能显著提高小鼠的免疫器官指数(P<0.05);显著促进小鼠的迟发型变态反应(p<0.05),提高小鼠脾淋巴细胞的增殖能力(P<0.05),提高小鼠的细胞免疫功能;提高血清溶血素含量(P<0.05),促进小鼠的体液免疫功能;显著促进小鼠的碳廓清能力(P<0.01)和腹腔巨噬细胞对鸡红细胞的吞噬率和吞噬指数(P<0.05, P<0.01),促进小鼠的非特异性免疫功能。9、在免疫肽的精制中,DA201-C树脂对PFH的吸附能力最强,静态吸附最佳条件为:温度25℃,pH 4.0,多肽浓度10 mg/mL,树脂质量与多肽体积比(g/mL) 2:1,吸附时间3 h,吸附率可达84.7%。乙醇浓度为50%(?)时,静态解析率最高为82.7%。动态吸附与解析得到的脱盐多肽,脱盐率为98.1%,多肽回收率为90.3%。脾细胞增殖实验表明DA201-C树脂脱盐后的多肽仍具有促进脾细胞增殖活性。

【Abstract】 Immunomodulating peptide can enhance the immunity of organism, the phagocytose ability of macrophages, and ability of anti-infection, which exhibited the many advantages such as the low molecular mass, good stability, weak immunogenicity, high biological activity and so on. Recently the study of bioactive peptides mainly focused on the optimization of bioactivities and kinetic model, while neither of them could confirm that the hydrolysis reaction was conducted as expected. In order to achieve the accurate prediction, dynamic monitoring and controlled hydrolysis during the preparation process of immunomodulating peptide, biotechnology, biosensors, mathematical model, and artificial neural network were used in the study. The bioactive peptides were refined by the resin. It could provide a theoretical basis and technological support for industrialization of immunomodulating peptide. In addition, the immune mechanism of bioactive peptides was also studied.The research results of this study were as follows:1、The Alaska Pollock frame (APF) was used as research materials and the main compositions were determined. The crude protein level of APF was high, with the content of 18.4%, which mainly consisted of alkali-soluble protein (35.49%) and stromatin (30.49%). It exhibited the high level of Gly (26.51%) and Glu (12.57%), followed by Ala, Asp, Ser, Leu and Lys. In order to make full use of APF, high- pressure cooking was set at 120℃for 30 min2、Degree of hydrolysis values, molecular weight distribution, and peptide levels were the important factors that reflected the characteristics of the hydrolysates, but it was difficult to monitor them online. Free amino acid levels of APF hydrolysates showed regular changes and can be used as response factor for indicating DH. They can be detected by biosensor, monitor the hydrolysis reaction. The advantage of the biosensor response factor is fast, high accuracy, good stability. To the measurements of glutamic acid and lysine, the relative error were 1.5% and 1.0%, coefficient of variation were 3.85% and 3.03%, the standard deviation are 0.78 and 0.60, respectively. Although seven enzymes were used for hydrolysis, free glutamic acid and lysine were changed regularly, and positively related to degree of hydrolysis, which can be used as hydrolysates response factor, while within a certain degree of hydrolysis, free glutamate and lysine acid concentration and the degree of hydrolysis showed a good linear relationship. It’s feasible to using the concentration of free glutamic acid and lysine as the response factors to monitor the degree of hydrolysis.3、It was confirmed that APF trypsin hydrolysates could enhance spleen lymphocyte proliferation, T lymphocyte proliferation, and phagocytic activity of macrophages (p<0.05) significantly. The molecular mass and degree of hydrolysis (DH) were important factors effecting on spleen lymphocyte proliferation. The highest proliferation ratio was reached in the range of 15-18%. APF was hydrolyzed by trypsin treatments to obtain immune activity polypeptides. The optimum parameters of hydrolysis were obtained by response surface methodology (RSM) as follows: fish protein concentration of 25g/L, pH 8.0, 50.0℃, time 290min, and [E]/[S] 24 U/mg, respectively. The average DH of five verification tests was 16.87% and the average spleen lymphocyte proliferation was 28.45%, which was in agreement with theoretical value. The immune activity peptide (PFH) was characterized in this study. It exhibited a maximum absorbance at 220 nm and 280nm and was rich in PRO levels (15.69%). PFH showed good solubility over a wide pH range and low viscosity in the range of 20-60℃; It showed significantly effect of pH on foaming properties and emulsifying characteristics. Although PFH had a little change which was treated by pepsin, trysin, and complex enzymes, the main composition was very similar to that of PFH before treatment.4、The kinetic model can reflect the hydrolysis process when the hydrolysis condition was constant. The kinetic model of APF and parameter of controlled- enzymatic hydrolysis were obtained by mathematic deduction and experimental analysis. The kinetic formulas were as follows: R= (0.1693 E0– 0.2816 S0) exp│-0.357 * DH│, DH= 2.801 ln│1 + (0.06044 E0/S0– 0.1005)t│, deactivation rate constant Kd was 0.0512 min-1. The kinetic model of PFH was as follows: DH= 2.801 ln [1+ 1.35006t].The preparation time of PFH can be obtained by its kinetic model, so it was very important for its preparation. The verification tests showed that the kinetic model could predict the hydrolysis process of PFH under constant condition. However, the hydrolysis conditions such as changes of stirring rate and temperature, were varied, and had significantly effect on final hydrolysates. Therefore, it was necessary to monitor the hydrolysis process online for the maximum immune activity peptide content in finally hydrolysates.5、The biosensor was used in the study for monitoring preparation of the immunodulating peptide of Alaska pollock frame under the constant and dynamic condition. It exhibited the good linear relations between degree of hydrolysis and free lysine and free glutamic acid when DH was in the range of 11-18% under constant condition. The formulas were as follows: DH = 0.2225[Glu] - 5.3097,DH = 0.0126 [Lys] - 1.2275. The mathematical relationship between concentrations of glutamic acid and lysine and DH was not ambiguity and it showed the ruleless curve relation when the initial enzyme concentration and initial substrate concentration were varied. Although they could not depict the relationship using the uniform mathematical model, the critical value of the hydrolysis reaction exhibited the good linear relationship and the formulas were as follows: [Glu] = 0.8186 [S0] + 0.0346 [E0] + 0.4506,[Lys] = 0.7430 [S0] + 0.1370 [E0] + 5.2931.6、The three network models were established for monitoring preparation of immune activity peptide under the dynamic condition including GLU-BP-ANNs LYS-BP-ANNs and GLU-LYS- BP- ANNs. They were based on BP-ANNs and biosensor. The response factors were included free Glu、Lys、Glu-Lys and so on. Comparative analysis of sample value and simulation value showed that R2 values were 0.9967、0.9964 and 0.9967,simulation error ranges were 0-4.14%、0-4.56% and 0-4.71%,simulation average error values were1.06%、0.94% and 0.99%。The verification tests of the three network models (five times for each) showed that they had a good reliability, and the theoretical value was in agreement with experimental value. The relative error ranges were 0.23%-2.81%,0.26%-1.91% and 0.30%-2.35%, respectively. Therefore the three network model can monitor the hydrolysis of Alaska Pollock frame under the dynamic conditions. The common parameters of the three models were as follows: one hidden layer, transfer function logsig in layer one, transfer function purelin in layer two, training function trainlm, adaptation learning function learngdm. The other parameters of GLU-BP-ANNs were as follows: input layer nodes were initial enzyme concentration E0, initial substrate concentration S0, and free glutamic acid concentration [Glu]; the number of output layer nodes was 10. The other parameters of LYS-BP-ANNs were as follows: input layer nodes were initial enzyme concentration E0, initial substrate concentration S0, and free lysine concentration [LYS]; the number of output layer nodes was 11. The other parameters of GLU-LYS-BP-ANNs were as follows: input layer nodes were E0, S0, [LYS] and [Glu]; the number of output layer nodes was 8.7、Three immune activity peptides were isolated from the Alaska pollock frame trypsin hydrolysates, using the chromatographic methods including Sephadex G-25 gel filtration chromatography, SP Sephadex C-25 ion-exchange chromatography and reversed phase high-performance liquid chromatography. The purity of immunomodulating peptide was measured using RP-HPLC equipped the Zorbax SB C18 analysis column. The sequences of peptide were identified by Nano-ESI-Ms/Ms as follows. The sequence of Immunomodulating peptide Y3 was Asn– Gly– Met– Thr– Tyr with molecular mass of 583.9922Da, and the spleen lymphocyte proliferation ratio treated by Y3 was 35.92%. The sequence of Immunomodulating peptide H2 was Asn– Gly– Leu– Ala– Pro with molecular mass of 470.1422Da, and the spleen lymphocyte proliferation ratio treated by H2 was 32.96%. The sequences of peptide were identified by Nano-ESI-Ms/Ms as follows. The peptide molecular mass and sequence of S4 was Trp-Thr and 305.1622Da, with the spleen lymphocyte proliferation ratio was 31.35%.8、The effects of PFH on immunomodulatory activities in normal and immunodepression mice were investigated by oral administration. PFH enhanced spleen lymphocyte transformation(P<0.05)、the delayed-type hypersensitivity (p<0.05) and the phagocytic index and rate of macrophages(P<0.05) significantly in normal mice (P<0.05), however, PFH showed the limited effects on the immune organ index and the hemolysin content (p>0.05). In hypoimmune mice, PFH increased the immune organ index (p<0.05). PFH could heighten the delayed-type hypersensitivity level (p<0.05)and spleen lymphocyte transformation (P<0.05), and it was indicated that PFH enhanced the function of cellular immunity in hypoimmune mice.In addition, PFH could increase the hemolysin content (P< 0.05) and promote the humoral immunity of hypoimmune mice. PFH also could enhance the ability of macrophages for carbon particle clearance (P< 0.01)and the phagocytic index and rate (P< 0.05, P< 0.01) significantly, and it was indicated that PFH could non-specific immunity in immunodepression mice.9、The adsorbing capacity of DA201-C resins was best. The highest adsorbing rate was 84.7% under 25℃, pH 4.0, the solution 10 mg/mL, and the ratio of resin mass to the volume of peptide 2:1 (g/mL). The highest rate of desorption (82.7%) was reached at the ethanol concentration of 50%. In dynamic adsorption and desorption, the results showed that the desalting and recovery rates of peptides were 98.1% and 90.3%, respectively. The sample desalted by DA201-C resin could enhance the splenocyte proliferation in a dose-dependent manner.

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