Protein Profiles of Human Serum by SELDI-TOF-MS with Multiwalled Carbon Nanotubes as Absorbent

The present paper describes a biomarker capturing strategy based on the enrichment efficiency of multiwalled carbon nanotubes (MWCNTs) for peptides and proteins from human serum. The method is shown to enrich proteins/peptides, and the captured molecules were profiled using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Mass spectra of the MWCNTs-treated human serum samples showed a significant enrichment of proteins by MWCNTs. Preliminary results indicated a good level of reproducibility in serum profiles with coefficients of variation (CVs) on signal intensity ranging from 8.9% to 25.2%. The developed method holds promise for improving the discovery of low-abundance serum biomarkers.     

Profiling of rat plasma by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry, a novel tool for biomarker discovery in nutrition research

The recent development of high-throughput proteomic technologies has given us new methods to analyze how an organism responds to changes in its nutritional environment. The analysis of plasma samples by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) was investigated as a novel approach to the identification of new biomarkers of nutrient status. Pre-fractionation of rat plasma by anion-exchange chromatography in 96-well filter plates markedly increased the total number of unique peptides and proteins that could be observed in SELDI-TOF mass spectra. Replicate fractionations generated nearly identical pH fractions, not only in terms of peptide and protein composition but also in respect to the ion signal intensity of replicate SELDI-TOF mass spectra. The feasibility of this approach was tested with samples from retinol-sufficient and retinol-deficient rats. The comparative analysis revealed reduced levels of three proteins with molecular masses between 10,000 and 20,000 in plasma of retinol-deficient rats. These results demonstrate that plasma profiling by anion-exchange fractionation and SELDI-TOF-MS may be a promising surveillance tool to detect changes in nutritional status and whole body physiology.     

由质谱分析数据建立乙肝病人与健康人的分类模型

建立运用表面加强激光解吸电离-飞行时间质谱获取乙肝病人和健康人血清蛋白指纹图谱数据,并用偏最小二乘(PLS)变量筛选法建立乙型肝炎(HBV)病人和健康人的分类模型,最终得到分类模型的交叉检验相关系数达0.97以上,判别准确率显著提高.对模型进行分析,找出对乙型肝炎病人和健康人的差异有重要影响的因素或变量.这些变量为某些质荷比区间内特定蛋白的峰强度值,反映这些质荷比区间内蛋白量的增加或减少,与乙肝病的形成有密切关系,可作为重要的生物标志物,进一步加以研究.本研究采用所得模型的拟合值等一些信息来做分类图,能较好地表达回归模型的分类效果.     

Serum Protein Profiling of Cervical Cancer Patients Using Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Using surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) technology, serum protein profiling was screened for the discovery of differentially expressed proteins between cervical cancer patients and control samples. Proteins and peptides in serum were captured by a CM10 proteinchip, and then detected by a proteinchip reader. The resulting profiling of all collected samples was analyzed with proteinchip software. Seven protein peaks were significantly regulated between the cancer group and the control group (p < 0.05). Fifty-three peaks in the m/z range from 2 kDa to 20 kDa were selected for partial least squares discriminant analysis (PLS-DA). The diagnostic model can distinguish cervical cancer in the blind test set from health controls with an accuracy of 90%. The combination of SELDI-TOF-MS and PLS-DA model can be used to screen significant proteins of differential expression in the serum of cervical cancer and may play a potential role in the diagnostics of cervical cancer.     

Computational modeling of the human serum proteome response to colon resection surgery

Principal component analysis (PCA) is much used in exploring time-course biological data sets, but does not distinguish variation between time and subjects. This study proposes a new integrated approach by combining analysis of variance (ANOVA) and three component modeling methods. The former was used to separate the between- and within-subject variation, and the latter represent modeling strategies on a scale moving from commonality to individuality. The proposed approach was applied to a surface-enhanced laser desorption and ionization time of flight mass spectrometry (SELDI-TOF-MS) data set of a serum protein expression time course before and after colon resection. Two common biological processes are identified and individual differences among patients were also detected, and the biological relevance of both is discussed.     

多壁碳纳米管对质谱分析中的血清蛋白富集作用研究

通过多壁碳纳米管(MWCNTs)对临床血清蛋白提取物进行富集处理,经表面增强激光解析离子化飞行时间质谱(SELDI-TOF-MS)检测,发现MWCNTs对血清中小分子量蛋白(<20 kDa)具有很好的富集效果。同时还考察了内径、长度等参数对血清蛋白富集效果的影响。该方法可用于临床血清样本中低丰度的小分子量蛋白的检测。     

Direct antigen detection from immunoprecipitated beads using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry; a new method for immunobeads-mass spectrometry (iMS)

One-step detection of biological molecules is one of the principal techniques for clinical diagnosis, and the potential of mass spectrometry for biomarker detection has been a promising new approach in the field of medical sciences. We demonstrate here a new and high-sensitivity method that we termed immunobeads-mass spectrometry (iMS), which combines conventional immunoprecipitation and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The key feature of iMS is the MS-compatible condition of immunoprecipitation using detergents with a monosaccaride-C8 alkyl chain or a disaccharide-C10 alkyl chain, and the minimized number of steps required for high-sensitivity detection of target peptides in serum or biological fluid. This was achieved by optimizing the wash buffer and subjecting the immunobeads directly to MALDI-TOF MS analysis. Using this method, we showed that 1 fmol of amyloid beta peptide spiked in serum was readily detectable, demonstrating the powerful tool of iMS as a biomarker detection method.     

Review of a current role of mass spectrometry for proteome research

This review is intended to give readers a snapshot of current mass spectrometry for proteomics research. It covers a brief history of mass spectrometry proteomic research, peptidomics and proteomics for biomarker search, quantitative proteomics, proteomics with post-translational modification and future perspective of proteomics.     

Targeted Metabolomics for Biomarker Discovery

Metabolomics is a truly interdisciplinary field of science, which combines analytical chemistry, platform technology, mass spectrometry, and NMR spectroscopy with sophisticated data analysis. Applied to biomarker discovery, it includes aspects of pathobiochemistry, systems biology/medicine, and molecular diagnostics and requires bioinformatics and multivariate statistics. While successfully established in the screening of inborn errors in neonates, metabolomics is now widely used in the characterization and diagnostic research of an ever increasing number of diseases. In this Review we highlight important technical prerequisites as well as recent developments in metabolomics and metabolomics data analysis with special emphasis on their utility in biomarker identification and qualification, as well as targeted metabolomics by employing high‐throughput mass spectrometry.     

Aptamer-facilitated biomarker discovery (AptaBiD)

Here we introduce a technology for biomarker discovery in which (i) DNA aptamers to biomarkers differentially expressed on the surfaces of cells being in different states are selected; (ii) aptamers are used to isolate biomarkers from the cells; and (iii) the isolated biomarkers are identified by means of mass spectrometry. The technology is termed aptamer-facilitated biomarker discovery (AptaBiD). AptaBiD was used to discover surface biomarkers that distinguish live mature and immature dendritic cells. We selected in vitro two DNA aptamer pools that specifically bind to mature and immature dendritic cells with a difference in strength of approximately 100 times. The aptamer pools were proven to be highly efficient in flow- and magnetic-bead-assisted separation of mature cells from immature cells. The two aptamer pools were then used to isolate biomarkers from the cells. The subsequent mass spectrometry analysis of the isolated proteins revealed unknown biomarkers of immature and mature dendritic cells.