Simultaneous assessment of average fragment size and amount in minute samples of degraded DNA

There is currently no method allowing routine characterization of minute amounts of degraded DNA samples such as those encountered in forensic science, archived tissues, ancient DNA, extracellular or stool DNA, and processed food. Here we describe and directly validate such a method based, on the one hand, on a generalized DNA random fragmentation model and, on the other, on two quantitative polymerase chain reaction (PCR) experiments using two different target sizes. The model also makes it possible to determine the minimum sample amount, the minimum mass average fragment size, and the maximum degradation time necessary to obtain a positive PCR.     

A Stereological Approach for Estimation of Cellular Immunogold Labeling and Its Spatial Distribution in Oriented Sections Using the Rotator

Particulate gold labeling applied to ultrathin sections is a powerful approach for locating cellular proteins and lipids on thin sections of cellular structures and compartments. Effective quantitative methods now allow estimation of both density and distribution of gold labeling across aggregate organelles or compartment profiles. However, current methods generally use random sections of cells and tissues, and these do not readily present the information needed for spatial mapping of cellular quantities of gold label. Yet spatial mapping of gold particle labeling becomes important when cells are polarized or show internal organization or spatial shifts in protein/lipid localization. Here we have applied a stereological approach called the rotator to estimate cellular gold label and proportions of labeling over cellular compartments at specific locations related to a chosen cell axis or chosen cellular structures. This method could be used in cell biology for mapping cell components in studies of protein translocation, cell polarity, cell cycle stages, or component cell types in tissues. (J Histochem Cytochem 57:709–719, 2009)     

Activity profiling of platelets by chemical proteomics

Chemical proteomics or activity based proteomics is a functional proteomics technology where molecular probes are used to target a selective group of functionally related proteins. Its emergence has enabled specific targeting of subproteomes, overcoming the limitations in dynamic range of traditional large‐scale proteomics experiments. Using a chemical proteomics strategy, we attempt to differentially profile the nucleotide‐binding proteome of active and resting platelets. We apply an affinity chromatography protocol using immobilized adenosine triphosphate, cyclic adenosine monophosphate, and cyclic guanosine monophosphate. The specificity of the immobilized nucleotides was demonstrated by competitive assays and by immunoblotting. LC coupled MS/MS was applied to identify the proteins recovered by our chemical proteomics strategy. When compared to a standard set of platelet lysate proteins, we confirmed that enrichment for nucleotide‐binding proteins was indeed taking place. Finally, by employing label‐free MS‐based comparative quantification, we found a small number of platelet proteins that show statistically significant difference between the active and resting nucleotide‐binding proteome.     

Combining selected reaction monitoring with discovery proteomics in limited biological samples

Simultaneous quantification of multiple proteins by selected reaction monitoring (SRM) has several applications in cell signaling studies including embryo proteomics. However, concerns have recently been raised over the specificity of SRM assays due to possible ion redundancy and/or sequence similarity of selected peptide with multiple non‐related proteins. In this Viewpoint article, we discuss some simple measures that can increase our confidence in the accuracy of SRM scans used in proteomic experiments. At least in embryonic samples from porcine species, these measures were found to be useful in validating MS‐identified differentially expressed proteins. Among the nine proteins analyzed by SRM assay, all the proteins that were found to be up‐ or down‐regulated in MS experiment were also faithfully up‐ or down‐regulated in SRM assay.     

Dynamic monitoring of changes in endothelial cell-substrate adhesiveness during leukocyte adhesion by microelectrical impedance assay

Adhesion of leukocytes to endothelial cells in inflammation processes leads to changes of endothelial cellsubstrate adhesiveness, and understanding of such changes will provide us with important information of inflammation processes. In this study, we used a noninvasive biosensor system referred to as real-time cell electronic sensor （RT-CES） system to monitor the changes in endothelial cell-substrate adhesiveness induced by human monoblastic cell line U937 cell adhesion in a dynamic and quantitative manner. This assay, which is based on cell-substrate impedance readout, is able to monitor transient changes in cell- substrate adhesiveness as a result of U937 cell adhesion. The U937 cell adhesion to endothelial cells was induced by lipopolysaccharide （LPS） in a dose-dependent manner. Although the number of adherent U937 cells to the endothelial cells was verified by a standard assay, the adhesiveness of endothelial cells after addition of U937 cells was monitored by the RT-CES system. Furthermore, focal adhesion kinase protein decrease and F-actin rearrangement in endothelial cells were observed after addition of U937 cells. Our results indicated that the adhesion of U937 cells to LPS-treated endothelial cells reduced the substrate, and such infiltration of leukocytes. the cell adhesiveness to reduction might facilitate     

Chemical proteomic and bioinformatic strategies for the identification and quantification of vascular antigens in cancer

One avenue towards the development of more selective anti-cancer drugs consists in the targeted delivery of bioactive molecules to the tumor environment by means of binding molecules specific to tumor-associated markers. In this context, the targeted delivery of therapeutic agents to newly-formed blood vessels (“vascular targeting”) is particularly attractive, because of the dependence of tumors on new blood vessels to sustain growth and invasion, and because of the accessibility of neo-vascular structures for therapeutic agents injected intravenously. Ligand-based vascular targeting strategies crucially rely on good-quality vascular tumor markers. Here we describe a number of established technologies for the enrichment of accessible vascular proteins based on the isolation of glycoproteins, the in vivo coating of accessible cell surfaces with colloidal silica and the in vivo perfusion with reactive ester derivatives of biotin. Label-free as well as isotopic labeling based strategies for the subsequent MS-based protein quantification are outlined. Finally, bioinformatic workflows for protein quantification are depicted aiming at assisting in the evaluation of appropriate strategies for individual projects. This review gives an overview of current chemical proteomic strategies for the enrichment and quantification of the accessible vascular proteome and helps in selecting bioinformatic strategies for data analysis and validation.     

与胃癌相关的几个量化掌褶纹特征的初步研究

本文对几个与胃癌的发生具有相关性的掌褶纹特征量进行了提取, 并与对照组进行了对比, 用统计学t检验的方法分析后发现,胃癌患者双手手掌掌褶纹的ATD角、左右手三线与掌宽夹角及左右手a-b嵴线数(a-bRc)与正常对照组之间均存在统计学意义上的差异, 这些结论为后期构建与胃癌的发生具有相关性的皮纹特征量化指标体系提供了依据,也为临床对早期胃癌患者的筛查提供了皮纹学方面的支持。     

Recent progress in liquid chromatography-based separation and label-free quantitative plant proteomics

Recent innovations in liquid chromatography-mass spectrometry (LC-MS)-based methods have facilitated quantitative and functional proteomic analyses of large numbers of proteins derived from complex samples without any need for protein or peptide labelling. Regardless of its great potential, the application of these proteomics techniques to plant science started only recently. Here we present an overview of label-free quantitative proteomics features and their employment for analysing plants. Recent methods used for quantitative protein analyses by MS techniques are summarized and major challenges associated with label-free LC-MS-based approaches, including sample preparation, peptide separation, quantification and kinetic studies, are discussed. Database search algorithms and specific aspects regarding protein identification of non-sequenced organisms are also addressed. So far, label-free LC-MS in plant science has been used to establish cellular or subcellular proteome maps, characterize plant-pathogen interactions or stress defence reactions, and for profiling protein patterns during developmental processes. Improvements in both, analytical platforms (separation technology and bioinformatics/statistical analysis) and high throughput nucleotide sequencing technologies will enhance the power of this method.