基于特征肽段的液相色谱-质谱技术鉴定胶原蛋白的物种来源

建立了一种基于特征肽段的液相色谱-质谱技术鉴定胶原蛋白物种来源的方法。样品经蛋白提取,还原,烷基化,胰蛋白酶消化后,采用Eksigent C18色谱柱(75μm×150 mm,3μm)分离,用流动相0. 1%甲酸水-乙腈溶液(98∶2)和0. 1%甲酸乙腈-水溶液(98∶2)梯度洗脱,在正离子模式下,通过纳升电喷雾四极杆飞行时间质谱进行检测,数据经Protein PilotTM软件及blast分析,筛选出潜在的特征肽段。消化后的样品再采用Eclipse Plus C18色谱柱(2. 1 mm×100 mm,1. 8μm)分离,用流动相乙腈和1%甲酸水溶液梯度洗脱,在正离子模式下,通过电喷雾四极杆/线性离子阱串联质谱的多反应监测触发增强子离子扫描模式进行检测,进一步确认肽段的特异性。最终筛选并确证了3种猪源性胶原蛋白特征肽段,4种牛源性胶原蛋白特征肽段,1种羊源性胶原蛋白特征肽段。所筛选的特征肽段具有良好的耐热性,可为动物源性胶原蛋白鉴定提供一种特异性强、准确可靠的检测方法。     

血清磷酸化肽的分离富集和质谱定量及其作为潜在肿瘤标志物的评价

血清中磷酸化肽种类和浓度的变化既能反映人体内蛋白质水解酶活性的变化,又能反映蛋白质翻译后磷酸化的水平,业已成为肿瘤标志物寻找和发现的重要目标。因而,血清中磷酸化肽的鉴定及其定量分析在具有临床应用价值的肿瘤标志物的筛选与发现中起着重要作用。由于血清中的内源性磷酸化肽丰度极低,在质谱分析中的离子化效率不高,且受到来自高丰度非磷酸化肽和蛋白质的信号抑制及干扰,血清中磷酸化肽的质谱定量分析是分析化学研究中的一个巨大挑战。文章对血清磷酸化肽的分离富集、质谱定量分析及其作为肿瘤标志物的筛选和评价等3个方面的研究进展进行总结、评述,并展望该领域的未来研究趋势和应用前景。     

超高效液相色谱-串联质谱法鉴定驼乳及其制品中的动物源性成分

采用蛋白质组学技术建立了驼乳及其制品中的动物乳源性成分特异性肽生物标志物的鉴定方法。样品经脱脂、蛋白质提取、胰蛋白酶水解后，利用超高效液相色谱-四极杆/静电场轨道阱高分辨质谱仪(UHPLC-Q/Exactive-HRMS)和Protein Pilot软件，实现了多肽生物标记物的鉴定；然后通过基本局部比对搜索工具(BLAST)与Uniprot数据库对比分析，筛选出了骆驼、家牛、水牛、牦牛、山羊、绵羊、驴和马共8个物种的22条肽生物标志物；最后利用超高效液相色谱-三重四极杆质谱(UHPLC-QqQ-MS)系统对这22条特征性多肽进行验证，采用多反应监测(MRM)模式建立了定量方法。实验优化了骆驼奶中酪蛋白的预处理方法，如冷冻脱脂、沉淀蛋白试剂和复溶液的选择等，并建立了基于生物标志物肽测定牛和山羊奶/奶粉掺假骆驼奶/奶粉的无标记定量方法。将牛、山羊和骆驼奶/奶粉等比例混合，分别对牛和山羊的特征肽段进行检测，结果显示，该方法对掺假液体乳/固体奶粉样品显示出良好的线性关系，抗干扰能力强，灵敏度高，重复性好，液态奶和奶粉的掺杂结果均与理论值接近。另外，该方法还被应用于11种骆驼奶和奶粉中家牛、水牛...     

基于稳定同位素标记和平行反应监测的蛋白质组学定量技术用于肝癌生物标志物的筛选和验证

肝癌是全球第五大恶性肿瘤,其五年生存率极低,及早地发现与诊断对肝癌的临床治疗具有重要意义。通过结合体外稳定同位素标记的蛋白质组学相对定量技术和基于平行反应监测的靶向蛋白质组学定量技术,建立了一种癌症生物标志物的筛选和验证方法。该方法被用于肝癌组织的差异蛋白质筛选和后期验证,共筛选到70个在癌组织中显著变化的蛋白质,并对其中7个蛋白质进行了验证。所验证的蛋白质包括已在临床使用的肝癌标志物甲胎蛋白(AFP)和文献报道的潜在肝癌生物标志物热休克蛋白(HSP90)、脂肪酸结合蛋白5(FABP5)和乙醇脱氢酶4(ADH4),说明了该方法的可靠性。该文所筛选的差异蛋白质可以为肝癌生物标志物研究和临床验证提供参考;该方法还可用于其他癌症样品的差异蛋白质筛选和验证。     

阿尔兹海默症血清多肽组生物标志物研究

采用个体样品单独分析的方式分析, 比较9个健康对照者、10个阿尔兹海默症(Alzheimer′s disease, AD)患者和12个认知功能障碍(Mild cognitive impairment, MCI)患者的血清多肽组分析结果, 以寻找潜在的AD病生物标志物.结果表明, 高强度的α-2-巨球蛋白肽段VGFYESDVMGR与AD病晚期阶段密切相关, 而载脂蛋白 C-Ⅲ、组蛋白H1.2和组蛋白H1.4的大量降解, 则与中早期AD和认知功能障碍相关联;载脂蛋白 C-Ⅲ和组蛋白H1的降解肽段具有明显的阶梯序列特征, 但在不同样本中的分布具有一定偶然性.AD病发展的晚期与中早期的血清多肽组特征不同, 这4种蛋白质的降解有可能成为AD病潜在的生物标志物.研究结果也证明了, 归属于纤维蛋白原α链、胸腺素β-4和斑联蛋白等蛋白质的肽段是所有血清样本中的优势肽段.本研究提出了利用血清多肽组学方法辅助诊断AD病的方法, 为临床大规模验证提供了依据和参考.     

基于液相色谱-串联质谱法的肉类特征肽段鉴别及掺假测定

建立了液相色谱-串联质谱技术鉴别肉类特征肽段及定量检测羊肉中常见外源肉掺假的方法。样品经蛋白质提取、胰蛋白酶水解和固相萃取小柱净化后,利用超高效液相色谱-四极杆/静电场轨道阱高分辨质谱（UPLC-Q/Exactive-HRMS）和Proteinpilot软件,实现蛋白质和多肽的鉴定;再通过基本局部比对搜索工具（BLAST）与Uniprot数据库对比分析,筛选出羊肉、鸭肉、猪肉和鸡肉的20个物种特征性多肽标志物;最后利用高效液相色谱-三重四极杆质谱（UPLC-QqQ-MS）系统对羊肉、鸭肉、猪肉和鸡肉的特征性多肽进行了验证和多反应监测（MRM）定量研究。将鸭肉、猪肉和鸡肉分别按照质量分数为1%、5%、10%、20%、50%的比例掺加到羊肉中,得到鸭肉最低掺假检出限为0.25%、猪肉最低掺假检出限为0.17%、鸡肉最低掺假检出限为0.10%。     

全二维微柱液相色谱-质谱鉴定人胃癌组织中的差异蛋白质

构建了以阳离子交换色谱-反相色谱(SCX-RPLC)为分离模式的新型全二维微柱液相色谱-质谱分离平台.采用了醋酸铵缓冲液梯度洗脱,实现了第一维肽段的分步洗脱,洗脱的肽段经富集除盐后通过接口进入反相色谱微柱,通过线性梯度实现第二维进一步分离,最后进入质谱进行检测.采用此平台分析了人胃癌组织与正常组织提取蛋白质信息,其中正常胃组织鉴定蛋白质数为537个,而癌症组织鉴定蛋白质数目为506个.对胃癌和正常组织两种提取蛋白质酶解产物的蛋白质检索结果进行比较分析,将鉴定的蛋白质按照物理性质进行分布,找出正常组织与癌症组织间蛋白质差异,筛选出一种可能发生变异的癌症特有蛋白.     

血清中低分子量蛋白质的提取和鉴定

采用改进的圆盘凝胶电泳提取人血清中低分子量蛋白质, 去除了血清中分子量大于3×104的蛋白质, 将提取的低分子量蛋白质热变性后直接在溶液中酶解成肽, 经液相色谱-质谱分析, 并进行Mascot数据库检索, 确认出人血清中97种蛋白质.     

气相色谱-质谱对青霉素发酵中玉米浆潜在标志物的研究

基于气相色谱-质谱(GC-MS)结合正交偏最小二乘判别分析法(OPLS-DA),建立了筛选玉米浆中影响青霉素发酵效价的潜在标志物的方法.利用GC-MS获得玉米浆中44种物质,经过标准化、Pareto预处理后,通过OPLS-DA对样本进行模式识别,根据模型的载荷图和变量重要性因子(VIP)筛选出9个潜在的标志物,即亮氨酸、5-酮脯氨酸、天冬氨酸、柠檬酸、酪氨酸、丝氨酸、赖氨酸、苏氨酸和葡萄糖.结果表明,这些物质与青霉素的初级代谢和次级代谢密切相关,可以作为筛选青霉素发酵优质原料的潜在质量指标.     

CZE-ESI-MS联用测定小肽混合物的研究

研究肽的分离行为、测定方法及测定条件对蛋白质组学研究具有重要意义 .毛细管电泳 ( CE)作为一种高效、快速的分离方法 ,样品用量少 ,已被广泛应用于生物领域中 ,尤其是小肽和蛋白质的分离分析 .质谱 ( MS)能够进行微量鉴定 ,并提供精确的分子量和结构信息 ,使其成为小肽和蛋白质检测和序列测定的强有力的支撑技术之一 [1～ 3] .其中 ,电喷雾 ( ESI)质谱作为一种软电离技术 ,易与常规的高分辨率分离方法如高效液相色谱、毛细管电泳等实现在线联用 ,具有分离效率高、检测灵敏度高和样品定性方便等特点 ,因而在小肽和蛋白质的测定中得到广…     

Meat species identification by linear discriminant analysis of capillary electrophoresis protein profiles

The objective of this study was to utilize linear discriminant analysis (LDA) in the interpretation of capillary electrophoresis-sodium dodecyl sulfate polymer-filled capillary gel electrophoresis (CE-SDS) meat protein profiles for the identification of meat species. The specific objectives were 1) to collect quantitative data on water-soluble and saline-soluble proteins of different meat species obtained by CE-SDS and 2) to apply LDA on collected CE-SDS protein data for the development of a pattern recognition statistical model useful in the differentiation of meat species. Samples were raw beef top and eye round, boneless fresh pork ham and loin, turkey leg and breast meat, and mechanically deboned turkey meat collected on six different occasions, making a total of 42 samples. Additionally, 14 samples were used as test samples to determine the classification ability of the procedure. Quantitative protein data obtained by CE-SDS was used to generate separate LDA models for either water- or saline-soluble protein extracts. Although a saline solution was a more efficient meat protein-extracting agent, as shown by a higher total protein concentration and a larger number of peaks, water-soluble CE-SDS protein profiles gave more distinctive discrimination among meat species. The correct classification given by LDA on water-soluble protein data was 100% for all meat species, except pork (94%). Conversely, the correct classification on saline-soluble protein data was 88% for beef and mechanically deboned turkey meat, and 94% and 100% for turkey and pork meat, respectively. LDA proved to be a useful pattern recognition procedure in the interpretation of CE-SDS protein profiles for the identification of meat species.     

Detection of pork in heat-processed meat products by monoclonal antibody-based ELISA

An enzyme-linked immunosorbent assay (ELISA) using a monoclonal antibody to a porcine thermal-stable muscle protein was developed for detection of pork in cooked meat products. The assay specifically detects porcine skeletal muscle, but not cardiac muscle, smooth muscle, blood, and nonmuscle organs. No cross-reactivity was observed with common food proteins. Validity of the assay was evaluated with laboratory formulated and commercial meat samples. The detection limit was determined as 0.5% (w/w) pork in heterologous meat mixtures. Overall, intra- and inter-assay coefficients of variation were 5.8 and 7.9%, respectively. The accuracy in analyzing market samples was 100% as verified by product labeling and confirmed by a commercial polycolonal antibody test kit.     

Multispecies Identification of Oilseed- and Meat-Specific Proteins and Heat-Stable Peptide Markers in Food Products

Consumer demand for both plant products and meat products enriched with plant raw materials is constantly increasing. Therefore, new versatile and reliable methods are needed to find and combat fraudulent practices in processed foods. The objective of this study was to identify oilseed species-specific peptide markers and meat-specific markers that were resistant to processing, for multispecies authentication of different meat and vegan food products using the proteomic LC-MS/MS method. To assess the limit of detection (LOD) for hemp proteins, cooked meatballs consisting of three meat species and hemp cake at a final concentration of up to 7.4% were examined. Hemp addition at a low concentration of below 1% was detected. The LOD for edestin subunits and albumin was 0.9% (w/w), whereas for 7S vicilin-like protein it was 4.2% (w/w). Specific heat-stable peptides unique to hemp seeds, flaxseed, nigella, pumpkin, sesame, and sunflower seeds, as well as guinea fowl, rabbit, pork, and chicken meat, were detected in different meat and vegan foods. Most of the oilseed-specific peptides were identified as processing-resistant markers belonging to 11S globulin subunits, namely conlinin, edestin, helianthinin, pumpkin vicilin-like or late embryogenesis proteins, and sesame legumin-like as well as 2S albumins and oleosin isoforms or selected enzymic proteins.     

基于多肽标记物分析的肉制品掺伪定量检测技术

该文开发了一种基于多肽标记物分析的肉制品掺伪检测技术,可同时进行定性和定量分析。样品经蛋白质提取和胰蛋白酶消化后,采用高分辨质谱(HRMS)和生物信息学工具,寻找牛、鸡、鸭、猪和羊5种肉类的特异性热稳定多肽标记物。在多反应监测(MRM)模式下,通过高效液相色谱-串联四极杆质谱(HPLC-QQQ-MS)对这些标记物进一步验证。使用由两种不同质量分数的肉类混合物(0%～100%)建立定量校准曲线,测定低限可达1%。采用该方法对市售的实际样品进行测试,验证结果表明该方法是一种可靠、有效的肉制品鉴定手段,可同时用于生肉和熟肉掺伪的定量检测。     

Establishment of a multiplex-PCR detection method and development of a detection kit for five animal-derived components in edible meat

A multiplex polymerase chain reaction (PCR) detection method for the simultaneous detection of animal-derived components from deer, cow, sheep, pig and horse in edible meat was established, and a multiplex PCR detection kit for the rapid detection of animal-derived components was developed. According to the mitochondrial cytochrome b (Cyt b) gene of bovine species, sheep species, pig species and horse species and the mitochondrial cytochrome c oxidase subunit I (COX 1) gene of sika deer and red deer as the target gene sequences of primers, the specific primers of five different species were designed, the PCR system was optimized, and the multiplex PCR identification method of five animal-derived components was established. The minimum detection amount was determined by sensitivity test. The results showed that five meat specific amplification bands could be found at the same time in the same reaction system, including 173 bp fragment for venison, 148 bp for beef, 261 bp for pork, 100 bp for mutton and 424 bp for horse, indicating that the method is specific and stable. The minimum detection limit by this method was 1 ng/μL, showing a high sensitivity. According to the different sites in different areas of animal mitochondrial genes, a multiplex PCR detection method was established and a detection kit was developed, and the rapid, sensitive, stable and high-throughput detection of five animal-derived components and adulterated animal components in edible meat can be realized by using the kit.     

Determination of rendering plant sterilization conditions using a commercially available ELISA test kit developed for detection of cooked beef.

A commercially available enzyme-linked immunosorbent assay (ELISA) test kit developed for detection of cooked beef in meat samples was used to determine appropriate heat treatment of rendered materials. An improved extraction procedure increased the absolute difference in R-values between 2 rendered materials treated under different conditions (average temperature 129 and 134 degrees C, respectively). To evaluate the influence of the main sterilization parameters on ELISA results, a factorial design approach was used. The parameters investigated were temperature, time, particle size, and meat composition. Lean meat samples containing beef and pork were sterilized under strictly controlled conditions in a laboratory autoclave. The experiments demonstrated that the R-values obtained with the ELISA test kit for beef are strongly influenced by temperature and time, whereas particle size has a minor influence. The proportion of bovine material did not have any impact on R-values. Autoclave-processed lean meat samples were analyzed by using an ELISA test kit for pork, which was validated in a collaborative trial. The ELISA test kit for pork proved to be more sensitive for the investigated parameters, thus verifying and extending previous investigations.     

Rapid Full-Cycle Technique to Control Adulteration of Meat Products: Integration of Accelerated Sample Preparation,Recombinase Polymerase Amplification,and Test-Strip Detection

Verifying the authenticity of food products is essential due to the recent increase in counterfeit meat-containing food products. The existing methods of detection have a number of disadvantages. Therefore, simple, cheap, and sensitive methods for detecting various types of meat are required. In this study, we propose a rapid full-cycle technique to control the chicken or pig adulteration of meat products, including 3 min of crude DNA extraction, 20 min of recombinase polymerase amplification (RPA) at 39 °C, and 10 min of lateral flow assay (LFA) detection. The cytochrome B gene was used in the developed RPA-based test for chicken and pig identification. The selected primers provided specific RPA without DNA nuclease and an additional oligonucleotide probe. As a result, RPA–LFA, based on designed fluorescein- and biotin-labeled primers, detected up to 0.2 pg total DNA per μL, which provided up to 0.001% w/w identification of the target meat component in the composite meat. The RPA–LFA of the chicken and pig meat identification was successfully applied to processed meat products and to meat after heating. The results were confirmed by real-time PCR. Ultimately, the developed analysis is specific and enables the detection of pork and chicken impurities with high accuracy in raw and processed meat mixtures. The proposed rapid full-cycle technique could be adopted for the authentication of other meat products.     

Proteomics based on selecting and quantifying cysteine containing peptides by covalent chromatography

This paper describes a procedure in which cysteine containing peptides from tryptic digests of complex protein mixtures were selected by covalent chromatography based on thiol-disulfide exchange. identified by mass spectrometry, and quantified by differential isotope labeling. Following disruption of disulfide bridges with 2,2'-dipyridyl disulfide, all proteins were digested with trypsin and acylated with succinic anhydride. Cysteine containing peptides were then selected from the acylated digest by disulfide interchange with sulfhydryl groups on a thiopropyl Sepharose gel. Captured cysteine containing peptides were released from the gel with 25 mM dithiothreitol (pH 7.5) containing 1 mM (ethylenedinitrilo)tetraacetic acid disodium salt and alkylated with iodoacetic acid subsequent to fractionation by reversed-phase liquid chromatography (RPLC). Fractions collected from the RPLC column were analyzed by matrix-assisted laser desorption ionization mass spectrometry. Based on isotope ratios of peptides from experimental and control samples labeled with succinic and deuterated succinic anhydride, respectively, it was possible to determine the relative concentration of each peptide species between the two samples. Peptides obtained from proteins that were up-regulated in the experimental sample were easily identified by an increase of the relative amount of the deuterated peptide. The results of these studies indicate that by selecting cysteine containing peptides, the complexity of protein digest could be reduced and database searches greatly simplified. When coupled with the isotope labeling strategy for quantification it was possible to determine proteins that were up-regulated in plasmid bearing Escherichia coli when expression of plasmid proteins was induced. Up-regulation of several proteins of E. coli origin was also noted.     

1H-NMR-Based Metabolomics: An Integrated Approach for the Detection of the Adulteration in Chicken,Chevon, Beef and Donkey Meat

Meat is a rich source of energy that provides high-value animal protein, fats, vitamins, minerals and trace amounts of carbohydrates. Globally, different types of meats are consumed to fulfill nutritional requirements. However, the increasing burden on the livestock industry has triggered the mixing of high-price meat species with low-quality/-price meat. This work aimed to differentiate different meat samples on the basis of metabolites. The metabolic difference between various meat samples was investigated through Nuclear Magnetic Resonance spectroscopy coupled with multivariate data analysis approaches like principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA). In total, 37 metabolites were identified in the gluteal muscle tissues of cow, goat, donkey and chicken using ¹H-NMR spectroscopy. PCA was found unable to completely differentiate between meat types, whereas OPLS-DA showed an apparent separation and successfully differentiated samples from all four types of meat. Lactate, creatine, choline, acetate, leucine, isoleucine, valine, formate, carnitine, glutamate, 3-hydroxybutyrate and α-mannose were found as the major discriminating metabolites between white (chicken) and red meat (chevon, beef and donkey). However, inosine, lactate, uracil, carnosine, format, pyruvate, carnitine, creatine and acetate were found responsible for differentiating chevon, beef and donkey meat. The relative quantification of differentiating metabolites was performed using one-way ANOVA and Tukey test. Our results showed that NMR-based metabolomics is a powerful tool for the identification of novel signatures (potential biomarkers) to characterize meats from different sources and could potentially be used for quality control purposes in order to differentiate different meat types.     

Classification of lactate dehydrogenase of different origin by liquid chromatography-mass spectrometry and multivariate analysis

A method intended to serve as a multivariate quality control tool in the production of pharmaceutical proteins is presented. The method is based on multivariate analysis of peptide maps generated with liquid chromatography-mass spectrometry (LC-MS). Lactate dehydrogenase (LDH) from different species and tissues were used as model compounds in the study. The proteins were digested with Endoproteinase Lys-C before the LC-MS analysis. After data pretreatment of the peptide maps, successful classification of the LDHs were obtained by discriminant analysis with partial least squares regression and artificial neural networks. Further, principal component analysis was applied to visualize the relationships between the samples.