Science Letters:Serum protein fingerprinting coupled with artificial neural network distinguishes glioma from healthy population or brain benign tumor

To screen and evaluate protein biomarkers for the detection of gliomas (Astrocytoma grade Ⅰ-Ⅳ) from healthy individuals and gliomas from brain benign tumors by using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) coupled with an artificial neural network (ANN) algorithm. SELDI-TOF-MS protein fingerprinting of serum from 105 brain tumor patients and healthy individuals, included 28 patients with glioma (Astrocytoma Ⅰ-Ⅳ), 37 patients with brain benign tumor, and 40 age-matched healthy individuals. Two thirds of the total samples of every compared pair as training set were used to set up discriminating patterns, and one third of total samples of every compared pair as test set were used to cross-validate; simultaneously, discriminate-cluster analysis derived SPSS 10.0 software was used to compare Astrocytoma grade Ⅰ-Ⅱ with grade Ⅲ-Ⅳ ones. An accuracy of 95.7%, sensitivity of 88.9%, specificity of 100%, positive predictive value of 90% and negative predictive value of 100% were obtained in a blinded test set comparing gliomas patients with healthy individuals; an accuracy of 86.4%, sensitivity of 88.9%, specificity of 84.6%, positive predictive value of 90% and negative predictive value of 85.7% were obtained when patient's gliomas was compared with benign brain tumor. Total accuracy of 85.7%, accuracy of grade Ⅰ-Ⅱ Astrocytoma was 86.7%, accuracy ofⅢ-Ⅳ Astrocytoma was 84.6% were obtained when grade Ⅰ-Ⅱ Astrocytoma was compared with grade Ⅲ-Ⅳ ones (discriminant analysis). SELDI-TOF-MS combined with bioinformatics tools, could greatly facilitate the discovery of better biomarkers. The high sensitivity and specificity achieved by the use of selected biomarkers showed great potential application for the discrimination of gliomas patients from healthy individuals and glioma from brain benign tumors.

Application of serum protein fingerprinting coupled with artificial neural network model in diagnosis of hepatocellular carcinoma

Background Hepatocellular carcinoma tends to present at a late clinical stage with poor prognosis. Therefore, it is urgent to explore and develop a simple, rapid diagnostic method, which has high sensitivity and specificity for hepatocellular carcinoma at an early stage. In this study, the serum proteins in patients with hepatocellular carcinoma or liver cirrhosis and in normal controls were analysed. Surface enhanced laser desorption/ionization time-of-flight mass （SELDI-TOF-MS） spectrometry was used to fingerprint serum protein using the protein chip technique and explore the value of the fingerprint, coupled with artificial neural network, to diagnose hepatocellular carcinoma. Methods Of the 106 serum samples obtained, 52 were from patients with hepatocellular carcinoma, 22 from patients with liver cirrhosis and 32 from healthy volunteers. The samples were randomly assigned into a training group （n = 70, 35 patients with hepatocellular carcinoma, 14 with liver cirrhosis, and 21 normal controls） and a testing group （n = 36, 17 patients with hepatocellular carcinoma, 8 with liver cirrhosis, and 11 normal controls）. An artificial neural network was trained on data from 70 individuals in the training group to develop an artificial neural network diagnostic model and this model was tested. The 36 sera in the testing group were analysed with blind prediction by using the same flowchart and procedure of data collection. The 36 serum protein spectra were clustered with the preset clustering method and the same mass/charge （M/Z） peak values as those in the training group. Matrix transfer was performed after data were output. Then the data were input into the previously built artificial neural network model to get the prediction value. The M/Z peaks of the samples with more than 2000 M/Z were normalized with biomarker wizard of ProteinChip Software version 3. 1 for noise filtering. The first threshold for noise filtering was set at 5, and the second was set at 2. The 10% was the minimum threshold for clustering. The statistical analysis of the data of serum protein mass spectrum was performed in the groups （normal vs. hepatocellular carcinoma, and liver cirrhosis vs. hepatocellular carcinoma） with the t test. Results Comparison between the groups of hepatocellular carcinoma and normal control： The mass spectra from 56 samples （hepatocellular carcinoma and normal controls） in the training group were analysed and 241 peaks were obtained. In addition, 21 peaks from them were used for comparison between the groups of hepatocellular carcinoma and normal controls （P 〈 0. 01 ）. Only 2 peaks at 3015 M/Z and 5900 M/Z were selected with significant difference （P〈10^-9）. A model was developed based on these two proteins with different M/Z. It was confirmed that this artificial neural network model can be used for comparison between the groups of hepatocellular carcinoma and normal controls. The sensitivity was 100% （17/17） , and the specificity was 100% （ 11/11 ）. Comparison between the groups of hepatocellular carcinoma and liver cirrhosis： The mass spectra from 49 samples in the training group （including patients with hepatocellular carcinoma and liver cirrhosis ） were analysed and 208 peaks were obtained. In addition, 21 peaks from them were used for comparison between the groups of hepatocellular carcinoma and liver cirrhosis （P 〈0. 01）. Only 2 peaks at 7759 M/Z, 13134 M/Z were selected with significant difference （P 〈 10^-9）. A model was developed based on these two proteins with dfferent M/Z. It was confirmed that this artificial neural network model can be used for comparison between the groups of hepatocellular carcinoma and liver cirrhosis. The sensitivity was 88.2% （15/17） , and the specificity was 100% （8/8）. Conclusions The specific biomarkers selected with the SELDI technology could be used for early diagnosis of hepatocellular carcinoma.

响应面法优化金钱白花蛇蛋白质的酸提工艺

以金钱白花蛇为原料,通过酸提法提取金钱白花蛇中的蛋白质,以蛋白质得率为指标,在单因素试验基础上通过响应面法优化提取工艺,并对提取物进行指纹图谱分析。结果表明:最佳酸提条件为醋酸钠浓度0.20mol/L、料液比1∶40(g/mL)、提取时间6 h、提取温度45℃,在此条件下蛋白质得率为3.92%。指纹图谱分析表明,酸提法所得金钱白花蛇的蛋白质种类较丰富。

小儿伤科泡腾颗粒中维持骨重塑稳态的生物活性分子筛选分析

目的:筛选小儿伤科泡腾颗粒中维持骨细胞骨重塑稳态的潜在中药质量标志物(Q-Marker)。方法:采用超高效液相色谱-四极杆-飞行时间串联质谱(UPLC-Q-TOF-MS)方法对不同提取基相、批次的小儿伤科泡腾颗粒常温提取液进行活性化学药物成分色谱、质谱解析。阳性对照采用伊班膦酸钠,绘制小儿伤科泡腾颗粒UPLC-Q-TOF-MS指纹图谱,结合SwissADME在线开源数据库对各成分主峰主要分子成分进行鉴定。筛选差异性分子图谱并与骨细胞Dickkopf相关蛋白1(DKK1)进行分子对接虚拟适配,以结合能<-15.0 kJ/mol为筛选条件,筛选小儿伤科泡腾颗粒治疗闭合性骨折的潜在Q-Marker。结果:对我院多批次小儿伤科泡腾颗粒原材料进行随机分布组合,共制备得到24批次小儿伤科泡腾颗粒样品,样品相似度分布区间0.901~0.976,有效成分具备一致性。小儿伤科泡腾颗粒总离子流图分析结果显示,共鉴定出18个共有峰,鉴别明确12种化合物:(+)-荷包牡丹碱、齐墩果酸、1182-94-1、赤霉素A4、白桦脂酸、植物甾醇、硫酸黄连碱、T25789、芍药新苷、二氢血根碱、人参皂苷Rh2、盐酸异黄连碱。其中,(+)-荷包牡丹碱、齐墩果酸、1182-94-1、硫酸黄连碱、T25789、芍药新苷、二氢血根碱、人参皂苷Rh2、盐酸异黄连碱9种化合物筛选作为小儿伤科泡腾颗粒的潜在Q-Marker。结论:(+)-荷包牡丹碱、齐墩果酸、1182-94-1、硫酸黄连碱、T25789、芍药新苷、二氢血根碱、人参皂苷Rh2、盐酸异黄连碱可能是小儿伤科泡腾颗粒维持骨细胞骨重塑稳态的主要活性成分,具备抑制DKK1活性并加速骨细胞重建的分子学潜能,可作为小儿伤科泡腾颗粒治疗闭合性骨折损伤的潜在Q-Marker。

Proteomic mapping of secreted proteins of Trichoderma spp.

A series of highly taxonomically diverse Trichoderma strains were investigated using proteomic approaches, to investigate the utility of protein profiles as taxonomic markers and to identify proteins of potential economic importance. Initial studies have focused on a comparison of single strains of T. aureoviride, T. saturnisporum, T. polysporum, T. longbrachiatum and T. spirale, along with two strains of T. harzianum. All seven strains were grown in synthetic medium supplemented with 2%(w/v) glycerol, to maximize the diversity of extracellular protein production. Samples of secreted protein were separated by 2D gel electrophoresis and will be characterized by MALDI-TOF peptide fingerprinting.

Cloning, Expression and Characterization of Translationally Controlled Tumor Protein (TCTP) Gene from Flatfish Turbot (Scophthalmus maximus)

A full-length cDNA encoding translationally controlled tumor protein of marine flatfish turbot (Scophthalmus maximus), SmTCTP, was isolated with rapid amplification of cDNA Ends (RACE). SmTCTP consisted of a 5’ untranslated region (UTR) of 84 bp, a 3’ UTR of 451 bp and an open reading frame (ORF) of 513 bp, encoding a protein of 170 amino acid residues, which contained two signature sequences of TCTP family. The 5’UTR of SmTCTP started with a 5’-terminal oligopyrimidine tract (5’-TOP), a typical feature for translationally controlled mRNAs. The deduced amino acid sequence of SmTCTP was similar to the other known verte- brate TCTPs in a range of 58.8% to 64.1%. The length of fish TCTPs was diverse among species, e.g., TCTP of turbot and sea perch (Lateolabrax japonicus) is 170 aa in length, while that of zebrafish (Danio rerio) and rohu (Labeo rohita) is 171 aa in length. North- ern blot analysis revealed that SmTCTP has only one type of mRNA. Its expression level in albino skin was slightly higher than that in normal skin. We constructed the pET30a-SmTCTP expression plasmid. The recombinant protein of His-tag SmTCTP was over-expressed in E. coli, purified and identified with peptide mass fingerprinting. These results may pave the way of further inves- tigation of the biological function of TCTP in fish.

利用深度迁移学习靶向GPCRs的配体活性预测

G蛋白偶联受体(GPCRs)是最重要的药物靶标之一,约占市场上药物靶标的34%。药物发现过程中,配体生物活性的准确建模和解释对于筛选苗头化合物至关重要。研究表明,同源的G蛋白偶联受体能提升配体分子生物活性的预测性能和可解释性。提出了一种新的方法GLEM,用多任务下的深度迁移学习来预测配体的生物活性,并通过组稀疏来识别相关的关键子结构。GLEM方法在9组30个具有代表性的人类GPCR数据集上进行了实验,这些GPCRs涵盖了大部分人类GPCRs的子家族,每个GPCR数据集都包含60~3000个配体。实验结果表明,GLEM方法在绝大多数数据集中都获得了最好的性能。与单任务学习方法相比,GLEM方法在r2上平均提升了31.72%;与深度学习方法相比,GLEM方法在r2上平均提升了22.45%。此外,还评估了不同数量的训练样本对模型性能的影响,实验发现GLEM方法在小样本情况下表现最好。

基于MALDI-TOF-MS技术筛选及鉴定大曲中芽孢杆菌

该研究对基质辅助激光解吸电离-飞行时间-质谱(MALDI-TOF-MS)技术体系进行改进与优化,创新性地引入浓香型大曲中芽孢杆菌(Bacillus)的筛选及鉴定,并结合分子生物学技术对该技术鉴定结果进行验证。结果表明,采用传统微生物培养分离法从大曲中分离得到126株菌株,其中125株通过MALDI-TOF-MS技术筛选鉴定获得9.0以上可信度分值,其中目标菌株枯草芽孢杆菌(Bacillus subtilis)及地衣芽孢杆菌(Bacillus licheniformis)的鉴定结果与分子生物学鉴定结果一致,说明该技术历经5~6 d可以准确地完成大曲样品中目标菌株的筛选鉴定,比传统微生物筛选鉴定方法至少节约1~2周时间。因此,基于MALDI-TOF-MS技术参与复杂样品中目标菌株的筛选与鉴定是一条高效的、可行的路径。

基于羧基活化原理的潜血手印及蛋白手印显现研究

以绿色荧光染料为原料,依次通过硅烷化修饰、胺基化修饰、羧基化修饰等步骤制备出表面活化羧基修饰的绿色荧光染料。利用绿色荧光染料表面的活化羧基与潜血手印及蛋白手印中的胺基在温和条件下发生酰胺反应,实现了潜血手印及蛋白手印的高质量与高效率显现。优化了手印显现的最佳条件,并对手印显现的对比度、灵敏度、选择性、适用性进行考察。实验结果表明,手印乳突纹线产生了明亮的绿色荧光,与客体背景之间形成了足够的对比反差,具有较高的对比度;乳突纹线连贯,细节特征明显,汗孔特征清晰,具有较高的灵敏度;乳突纹线与小犁沟之间差异明显,具有较高的选择性;本方法适用于显现光滑非渗透性及半渗透性客体表面潜血手印及蛋白手印,具有较强的适用性。

僵蚕药材蛋白质分级指纹图谱建立及产地鉴定相关分子研究

建立云南与四川僵蚕药材的总蛋白质指纹图谱及分级指纹图谱,对比分析以发现其中的差异表达蛋白质分子并进行鉴定及生物信息学分析,探索其用于产地鉴定的可行性。提取两种僵蚕的酸溶、碱溶、水溶及醇溶性总蛋白质,对其进行丙酮分级沉淀,对所得样品进行SDS-PAGE指纹图谱对比分析,对所得差异条带进行LC-MS/MS分析,数据库检索后进行生物信息学分析。两种僵蚕的总蛋白质指纹图谱相似度很高,难以据此进行产地鉴定;两种僵蚕的分级指纹图谱则有较显著差异,有望用于产地鉴定;依据分级指纹图谱差异共鉴定出β-葡萄糖苷酶、抗胰凝乳蛋白酶、抗胰蛋白酶、含脂肪酶结构域蛋白等273种蛋白质。云南与四川僵蚕的蛋白质组成及其分级指纹图谱存在显著差异,有望用作产地鉴定的分子依据;醇溶蛋白质构建分级指纹图谱可以提供更加丰富的信息及更好的分辨率;分级指纹图谱技术具有简便易行、分辨率较高的优点,为其他中药材的产地鉴定研究提供了方法学思路。

白芷醇溶蛋白质提取工艺优化及其指纹图谱研究

目的:基于响应面设计优化白芷醇溶蛋白质提取工艺,并研究其指纹图谱特征。方法:首先考察液料比、提取时间、乙醇浓度、提取温度四个单因素对白芷醇溶蛋白质提取率的影响,再通过Box-Behnken方法对影响提取率的工艺因素进行响应面优化,最后对白芷及易混淆药材的醇溶蛋白质指纹图谱进行对比分析。结果:最佳提取工艺条件为:液料比13∶1(mL/g),提取时间8.75 h,乙醇浓度42%,提取温度45℃,在此条件下提取率为0.294%。SDS-PAGE分析表明白芷醇溶蛋白质样品分子量范围介于15~95 kDa,91.4 kDa与65.6 kDa分子为高丰度蛋白质。此外,白芷与天花粉、粉葛、山药的醇溶蛋白质指纹图谱有显著差异。结论:利用响应面法优化了白芷醇溶蛋白质的提取工艺,并建立其专属性SDS-PAGE指纹图谱,为其分子鉴定及资源开发提供实验依据。

乳蛋白高效液相色谱检测方法的优化及甘南牦牛乳指纹图谱的建立

建立多种乳蛋白同时检测的高效液相色谱法,为乳及乳制品乳蛋白的分离检测提供方法,并建立甘南牦牛乳的指纹图谱。样品采用缓冲液使蛋白溶解变性,采用高效液相色谱检测,ZORBAX 300SB-C8色谱柱,检测波长为214 nm,柱温40℃,流速0.6 mL/min,梯度洗脱。所建方法能够分离乳中的κ-酪蛋白、α-酪蛋白、β-酪蛋白、α-乳白蛋白、β-乳清蛋白,峰保留时间RSD<1.3%,峰面积RSD<3.3%。10批甘南牦牛乳样品得到的指纹图谱相似度大于0.99,指认了其中9个乳蛋白色谱峰。该方法操作简便、具有良好的重现性和专属性,适用于乳及乳制品中多种乳蛋白的分离检测。所建立的甘南牦牛乳指纹图谱为牦牛乳的质量控制提供参考依据。

基于红外指纹图谱的螺旋藻品质分析和蛋白含量测定

采用傅里叶变换红外光谱(FTIR)分析技术,对螺旋藻标准品、螺旋藻粉样品和糊精标准品的红外光谱进行分析。螺旋藻中的蛋白质(1 657,1 537cm-1)和糖类(1 069,1 054cm-1)具有明显的红外指纹特征。螺旋藻粉中的主要成分为蛋白质和糖类,主要辅料为糊精。比较28个不同厂家螺旋藻粉的红外指纹图谱,计算图谱相关系数确定出辅料添加比例的高低。建立吸收峰强度比和蛋白质含量的关联标准曲线,形成依据红外光谱测定样品蛋白含量的方法,与凯氏定氮法测定结果相对偏差小于5%,为螺旋藻粉品质鉴定提供了一种简便、快速、无损的新方法。

遗传标记及其在作物品种鉴定中的应用

本文评述了用于作物品种鉴定的形态标记 (morphologicalmarkers)、细胞标记 (cytologicalmarkers)、生化标记 (biochemicalmarkers)、分子标记 (molecularmarkers)的优缺点。重点评述了分子标记在作物品种鉴定中的应用。文中除对蛋白质电泳指纹图谱———同工酶和贮藏蛋白 (包括醇溶性蛋白、清蛋白、谷蛋白、球蛋白等 )电泳产生的指纹图谱的应用外 ,较详细地介绍了近年来DNA指纹图谱技术 ;包括限制片段长度多态性 (restrictionfragmentlengthpolymorphism ,简称RFLP)、随机扩增多态性DNA (randomamplifiedpolymorphicDNA ,简称RAPD)、小卫星DNA(minisatelliteDNA)、微卫星DNA(microsatelliteDNA) ,简单重复序列间扩增 (intersimplesequencerepeats,简称ISSR) ,扩增片段长度多态性 (amplifiedfragmentlengthpolymor phism ,简称AFLP)以及CAPS (cleavedamplifiedpolymorphicsequences)和SNPS (singlenucleotidepolymor phisms)对作物品种鉴定和新品种登记 ,品种纯度和真实性的检验以及品种间亲缘关系的探讨和在分类研究中的贡献等。

麦醇溶蛋白电泳技术在杂交小麦种子纯度鉴定中的应用

为了探索一种能准确用于鉴定杂交小麦种子纯度的方法与技术,采用种子醇溶蛋白酸性聚丙烯酰胺凝胶电泳(A-PAGE)技术对杂交小麦品种(组合)西杂一号、西杂三号和西杂五号进行分析,建立了西杂一号、西杂三号和西杂五号的标准图谱库,同时利用Gel 2.0软件建立了相应的模式图。人为混种试验结果表明,本研究得到的醇溶蛋白标准图谱可以用于鉴定杂交小麦种子的纯度。

应用蛋白质指纹图谱技术快速鉴别诊断菌阴肺结核

目的探索应用蛋白质指纹图谱技术于菌阴肺结核与肺炎的鉴别诊断。方法从本院临床病例中,选择菌阴肺结核和肺炎患者及健康者各60例,应用表面加强激光解吸电离飞行时间质谱技术(SELDI/ToF-Ms)和蛋白芯片技术检测血清蛋白,并应用Ciphergen蛋白芯片3.1.1软件进行比较,分析其相关蛋白峰值并进行统计学处理。结果对180例菌阴肺结核、肺炎患者、健康者的血清蛋白指纹图谱数据进行比较,发现有5个蛋白峰(1 028.49、4 796.56、7 564.77、8 048.02、11 526.75m/z)存在显著的差异,有统计学意义(P<0.01)。由这5个蛋白峰组成的诊断模型鉴别诊断菌阴肺结核与肺炎的总有效率84.2%(101/120),敏感性与特异性分别为82.5%(52/63),85.9%(49/57);阳性预测值86.7%(52/60),阴性预测值为81.7%(49/60)。诊断模型在判别肺炎、菌阴肺结核患者与健康者之间,总有效率达89.4%(161/180),特异性为100%(60/60),灵敏度为84.2%(101/120),阳性预测值100%(101/101),阴性预测值75.9%(60/79)。结论蛋白质指纹图谱技术具有方法简便、检测快速,标本用量少的优点,是筛选结核病特异性标志物的有效手段,通过蛋白质指纹图谱技术检测,发现了具有良好鉴别诊断的"诊断模型"。

新疆维吾尔族食管癌患者血清蛋白指纹图谱诊断模型的建立

目的:筛选并建立新疆维吾尔族食管癌血清蛋白指纹图谱诊断模型,为食管癌的诊断与临床筛查提供新的途径。方法:采用弱阳离子交换蛋白质芯片(CM10蛋白芯片)及表面增强激光解析离子化飞行时间质谱(SELDI-TOF-MS)技术对23例新疆维吾尔族食管癌和33例新疆维吾尔族正常对照者血清指纹图谱进行检测,所得结果用ZUCI-蛋白芯片数据分析系统(ZUCI-Protein Chip Data Analyze System)软件包进行分析,通过支持向量机运算建立区分新疆维吾尔族食管癌蛋白指纹图谱诊断模型,并用留一法交叉验证作用评估模型,判别效果。结果:通过软件包运算,用2个质荷比峰(3269.4621、6056.8714m/z)建立了新疆维吾尔族食管癌蛋白指纹图谱诊断模型,准确度为92.9%,灵敏度为91.3%,特异度为93.9%,阳性预测值为91.3%。结论:SELDI-TOF-MS技术结合支持向量机建立新疆维吾尔族食管癌血清蛋白质指纹图谱模型为早期筛查及诊断新疆维吾尔族食管癌提供了一种特异性强、灵敏度高的新方法,值得进一步的研究和应用。

肺结核蛋白指纹图谱诊断技术研究

目的探索应用蛋白质组学技术于肺结核诊断。方法从本院临床肺结核病例中,选择痰检测结核分枝杆菌培养阳性、阴性肺结核患者共130名,以健康者65名为对照,进行血清蛋白指纹图谱检测,分析其相关蛋白峰值并进行统计学处理。结果 130例活动性肺结核患者,与65名正常人群血清蛋白质质谱数据的比较,5个蛋白峰(5335、8048、11683、11700、11526m/z)有差异,有统计学意义(P<0.01)。该诊断模型判别的总准确率为92.3%(180/195),特异度100%(65/65),灵敏度88.5%(115/130)。130例活动性肺结核患者中,菌(+)65例,质谱仪检测结果峰值为:5335m/z24例,11683m/z16例,8048m/z14例,11700m/z5例,占90.8%(59/65);菌(-)65例,峰值为:8048m/z20例,5335m/z14例,11526m/z8例,11683m/z7例,11700m/z6例,占84.6%(55/65)。结论血清蛋白质指纹图谱技术简便、快速,标本用量少,是筛选结核病特异性标志物的有效手段,有望成为活动性肺结核的早期辅助诊断指标。

五种不同苜蓿的种子蛋白指纹图谱研究

采用8%和10%两个浓度梯度的SDS-聚丙烯酰胺凝胶电泳,对黄花苜蓿、天蓝苜蓿、一年生苜蓿(Orion)、紫花苜蓿(敖汉)及1个紫花苜蓿杂交种共5种不同苜蓿的种子可溶性蛋白和盐溶蛋白图谱进行了研究。结果显示:5个种10%和8%凝胶电泳的种子可溶性蛋白总带数分别为97和91,10%凝胶电泳的种子盐溶蛋白共有69条谱带;5种苜蓿在种子可溶性蛋白和盐溶蛋白电泳图上都具有各自的特征谱带,谱带数目、位置、宽窄和颜色深浅都存在明显的差异;10%凝胶的可溶性蛋白指纹图谱谱带数目相对较多,种间遗传差异在A、B、C区均有分布,谱带的重复性好,是鉴别种的最好图谱。5种苜蓿种子可溶性蛋白和盐溶蛋白指纹图谱一致,表明杂交种和敖汉苜蓿的谱带相似性最大,与黄花苜蓿的相似性次之,而这3个种与天蓝苜蓿和一年生苜蓿(Orion)的相似性较小。这与种在形态学上表现出来的差异相一致,从而进一步肯定了采用种子贮藏蛋白电泳技术进行苜蓿分类研究和种子鉴别的可靠性。

血液蛋白质组与质谱仪检测流程标准化初探

目的探讨不同的标本处理和储存条件对蛋白指纹图谱技术检测血清多肽及低分子量蛋白质(1-30 ku)的影响。方法将血液凝固后马上分离得到的血清分装后分别置于-80℃6个月以上以及室温、4℃条件下2-72 h进行蛋白质质谱分析。结果血清样本在-80℃6个月以上以及4℃或者25℃保存2 h或者反复冻溶1次,对多肽及低分子量蛋白质的影响相对较小。将血清用U9缓冲液稀释后放置于室温,在24 h内结果稳定。溶血会对蛋白质组的结果造成很大影响。结论建议血液标本的处理、运送、操作及储存的蛋白质质谱分析的标准条件是:4℃下处理血液标本,2 h内尽快分离血清及细胞。用U9缓冲液稀释血清后,可以24 h内在室温下运送或对血清及WCX磁珠结合过程进行操作。血清应分装并长期储存在-80℃,但限冻溶1次。溶血标本应弃用,建议重新取血。