Endogeneous peptide profiling of cerebrospinal fluid by MALDI-TOF mass spectrometry: Optimization of magnetic bead-based peptide capture and analysis of preanalytical variables

Cerebrospinal fluid (CSF) perfuses the brain and spinal cord. CSF contains peptides and proteins important for brain physiology and potentially also relevant to brain pathology. High-throughput endogeneous peptide profiling by MS is an emerging approach for disease diagnosis and biomarker discovery. A magnetic bead-based method for off-line serum peptide capture coupled to MALDI-TOF-MS has been introduced recently. In this study, we optimize the peptide capture method for profiling of CSF and investigate the effect of a number of preanalytical variables. The CSF profiles contain ～100 reliably detected peptides at m/z 800-4000 with reproducible ion intensities (average 7% CV). The investigated preanalytical variables include: time at room temperature (RT) before storage, storage temperature, freeze-thawing cycles, and blood contamination. The CSF peptidome (<20?kDa) is relatively stable and can withstand a few hours at RT and several freeze-thaw cycles. Several peptides sensitive to storage at -20°C, including Cystatin C, were assigned based on mass or identified by MS/MS. Hemoglobin α and β chains were detected in blood contaminated samples, at levels invisible to the eye (0.01%). These peptides may be used for quality control in a MALDI-TOF-MS screening strategy to select high quality samples for in-depth proteomics analysis in disease studies.     

Sera proteomic biomarker profiling in HIV-1 infected subjects with cognitive impairment

HIV-1 infection of the brain commonly leads to cognitive impairments (CIs). In its most severe form, HIV-1 associated dementia (HAD) is associated with advanced immune suppression and debilitating loss of memory, behavioral, and motor functions. Despite significant research activities, diagnosis remains one of exclusion. Bioimaging, neuropsychological testing, and viral and immune biomarkers serve to support but not define a diagnosis of HIV-1 associated CI. This is timely and required as brain injury triggered by HIV-1 can be controlled, in part, by antiretroviral medicines. The recent development of proteomics has opened new ways to study viral-host interactions which may provide new insight into treatment and disease monitoring. To this end, we developed a proteomics platform for HIV-1 associated CI biomarker discovery and used it to perform a pilot study for sera-associated HAD proteins. A 2-DE map of a serum proteome was focused on differentially expressed proteins. Differential expression of two proteins was validated by Western blot tests identifying afamin and ceruloplasmin as a potential biomarkers for CI associated with advanced HIV-1 infection.     

Understanding dendritic cell biology and its role in immunological disorders through proteomic profiling

Dendritic cells (DC) have always been present on the bright spot of immune research. They have been extensively studied for the last 35 years, and much is known about their different phenotypes, stimulatory capacity, and role in the immune system. During the last 15 years, great attention has been given to studies on global gene and protein expression profiles during the differentiation and maturation processes of these cells. It is well understood that studying the proteome, together with information on the role of protein post-translational modifications (PTM), will reveal the real dynamics of a living cell. The rapid increase of proteomic studies during the last decade describing the differentiation and maturation process in DCs, as well as modifications brought by the use of different compounds that either increase or decrease their immunogenicity, reflects the importance of understanding the molecular processes behind the functional properties of these cells. In the present review, we will give an overview of proteomic studies focusing on DCs. Thereby we will concentrate on the importance of these studies in understanding DC behavior from a molecular point of view and how these findings have aided in understanding the differences in functional properties of these cells.     

非相关线性判别分析用于蛋白质组数据的分类及特征挑选

提出一种非相关线性判别分析(ULDA)结合统计卡方检验(CHI2)的方法用于蛋白质组质谱数据的分类及特征挑选.首先以卡方检验为过滤器去除无类间差别的变量,然后用ULDA进行样本分类与特征筛选,通过对两组数据的分析,最终选择出的特征变量在这两组数据中的特异性分别为98.2%和95.74%,灵敏度均为100%.结果表明本文提出的方法能较好地处理变量数很大的蛋白质组数据,同时表明最后选择的特征变量有可能作为潜在的生物标记物,为相关疾病的早期诊断提供线索.     

Urinary proteomic analysis of chronic allograft nephropathy

The pathogenesis of progressive renal allograft injury, which is termed chronic allograft nephropathy (CAN), remains obscure and is currently defined by histology. Prospective protocol-biopsy trials have demonstrated that clinical and standard laboratory tests are insufficiently sensitive indicators of the development and progression of CAN. The study aim was to determine if CAN could be characterized by urinary proteomic data and identify the proteins associated with disease. The urinary proteome of 75 renal transplant recipients and 20 healthy volunteers was analyzed using surface enhanced laser desorption and ionization MS. Patients could be classified into subgroups with normal histology and Banff CAN grades 2-3 with a sensitivity of 86% and a specificity of 92% by applying the classification algorithm Adaboost to urinary proteomic data. Several urinary proteins associated with advanced CAN were identified including α1-microglobulin, β2-microglobulin, prealbumin, and endorepellin, the antiangiogenic C-terminal fragment of perlecan. Increased urinary endorepellin was confirmed by ELISA and increased tissue expression of the endorepellin/perlecan ratio by immunofluoresence analysis of renal biopsies. In conclusion, analysis of urinary proteomic data has further characterized the more severe CAN grades and identified urinary endorepellin, as a potential biomarker of advanced CAN.     

Protein profiling of formalin fixed paraffin embedded tissue: Identification of potential biomarkers for pediatric brainstem glioma

Little is known about the molecular characteristics of pediatric brainstem gliomas (BSG), which continue to have a dismal prognosis. Targeted molecular strategies are limited due to rarity of biopsy BSG specimen coupled with obstacles associated with the analyses of formalin-fixed paraffin-embedded (FFPE) autopsies. The objective of this study was to develop methodologies to successfully identify the proteome profile from these archived FFPE specimens. Peptides were extracted from both tumor and adjacent normal FFPE brainstem specimen and quantified using (18) O proteolytic labeling strategy and LC-MS/MS analysis. The ingenuity pathway analysis software was used to elucidate interactions amongst differentially expressed proteins. We identified 188 proteins of which 54 (29%) were found up-regulated (≥1.5-fold) in BSG compared to normal sections. Of these, 15 (28%) proteins have previously been reported as potential biomarkers for supratentorial malignant gliomas, while the rest appear to be exclusive to pediatric BSG. Because the majority of differentially expressed proteins are unique to BSG, we conclude that pediatric BSG is distinct from supratentorial gliomas. To the best of our knowledge, this is the first proteome profile of pediatric BSG, which may facilitate discovery of novel therapeutic targets for early diagnostics and improving prognostics.     

An application of the 2-nitrobenzenesulfenyl method to proteomic profiling of human colorectal carcinoma: A novel approach for biomarker discovery

In the development of novel biomarkers, the proteomic approach is advantageous because using it the cancer-associated proteins can be directly identified. We previously developed a 2-nitrobenzenesulfenyl (NBS) method to improve quantitative proteome analysis. Here, we applied this method to proteomic profiling of colorectal carcinoma (CRC) to identify novel proteins with altered expression in CRC. Each pair of tumor and normal tissue specimens from 12 CRC patients was analyzed, and approximately 5000 NBS-labeled paired peaks were quantified. Peaks with altered signal intensities (>1.5-fold) and occurring frequently in the samples (>70%) were selected, and 128 proteins were identified by MS/MS analyses as differentially expressed proteins in CRC tissues. Many proteins were newly revealed to be CRC related; 30 were reported in earlier studies of CRC. Six proteins that were up-regulated in CRC (ZYX, RAN, RCN1, AHCY, LGALS1, and VIM) were further characterized and validated by Western blot and immunohistochemistry. All six were found to be CRC-localized, either in cancer cells or in stroma cells near the cancer cells. These results indicate that the proteins identified in this study are novel candidates for CRC markers, and that the NBS method is useful in proteome mining to discover novel biomarkers.     

HPCVIEW: A Tool for Top-down Analysis of Node Performance

It is increasingly difficult for complex scientific programs to attain a significant fraction of peak performance on systems that are based on microprocessors with substantial instruction-level parallelism and deep memory hierarchies. Despite this trend, performance analysis and tuning tools are still not used regularly by algorithm and application designers. To a large extent, existing performance tools fail to meet many user needs and are cumbersome to use. To address these issues, we developed HPCVIEW—a toolkit for combining multiple sets of program profile data, correlating the data with source code, and generating a database that can be analyzed anywhere with a commodity Web browser. We argue that HPCVIEW addresses many of the issues that have limited the usability and the utility of most existing tools. We originally built HPCVIEW to facilitate our own work on data layout and optimizing compilers. Now, in addition to daily use within our group, HPCVIEW is being used by several code development teams in DoD and DoE laboratories as well as at NCSA.     

Parallel program analysis on workstation clusters: speedup profiling and latency hiding

Parallel programming on workstation clusters is subject to many factors and problems which determine the potential success or failure of any individual implementation. The most obvious problems are the difficulty in developing parallel algorithms and the high communication latency which may render such algorithms inefficient. In an attempt to address some of these issues we propose a strategy for estimating the potential speedup of a parallel program based on computation and communication profiling. We show that our proposed strategy yields accurate estimates of the speedup. We also propose a complete communication model so that the speedup can be estimated under different programming inputs and show that moderately accurate estimates can be obtained. High communication latency is the major problem with workstation cluster computing. We attempt to examine this problem from the system level point of view and show experimentally that latency hiding can allow almost full utilisation of the CPU resource even though individual programs may suffer from high communication latencies. © 1997 John Wiley & Sons, Ltd.     

HPCVIEW: A Tool for Top-down Analysis of Node Performance

It is increasingly difficult for complex scientific programs to attain a significant fraction of peak performance on systems that are based on microprocessors with substantial instruction-level parallelism and deep memory hierarchies. Despite this trend, performance analysis and tuning tools are still not used regularly by algorithm and application designers. To a large extent, existing performance tools fail to meet many user needs and are cumbersome to use. To address these issues, we developed HPCVIEW—a toolkit for combining multiple sets of program profile data, correlating the data with source code, and generating a database that can be analyzed anywhere with a commodity Web browser. We argue that HPCVIEW addresses many of the issues that have limited the usability and the utility of most existing tools. We originally built HPCVIEW to facilitate our own work on data layout and optimizing compilers. Now, in addition to daily use within our group, HPCVIEW is being used by several code development teams in DoD and DoE laboratories as well as at NCSA.     

Using bioinformatic resources in the proteomic analysis of biological fluids

On-line databases targeted towards protein contents in biological fluids are scarce. Consequently, the investigation of proteins identified in a biological fluid most importantly depends on crosschecking information gathered from less specific resources. This review summarises the key databases and tools for collecting information on tissue specificity or expression profiles. It also emphasises the high connectivity between databases fruitfully used to corroborate and piece information together. Finally, selected issues related to appropriate bioinformatics tools in the context of clinical applications are succinctly discussed.     

Mitigating insider threat by profiling users based on mouse usage pattern: ensemble learning and frequency domain analysis

International Journal of Information Security - Exploring novel security layers in academia and industry is always a concern due to the types of malware developing currently. Adding a widely...     

Expression of tropomyosin alpha 4 chain is increased in esophageal squamous cell carcinoma as evidenced by proteomic profiling by two-dimensional electrophoresis and liquid chromatography-mass spectrometry/mass spectrometry

To identify proteins associated with esophageal carcinogenesis, we performed protein profiling of 16 esophageal squamous cell carcinomas (ESCCs) and paired noncancerous tissues by 2-DE and MS/MS. In cancerous tissues, three spots showed significant up-regulation in the amount of protein, while eight spots were significantly down-regulated. The identities of the spots were determined by PMF with LC-MS/MS and were confirmed by immunoblotting. The up-regulated proteins were tropomyosin alpha 4 chain, transgelin, and pyruvate kinase. The down-regulated proteins were serum albumin precursor, isoforms of annexin A1, tropomyosin beta chain, 14-3-3 protein sigma, and isoforms of serotransferrin precursor. In all 16 cases, up-regulation of the tropomyosin alpha 4 chain was confirmed by immunoblotting. Localization of the tropomyosin alpha 4 chain in ESCC cells and adjacent fibroblasts was confirmed by immunohistochemistry.